0–200 mMOFOMO and OcéanIA
Publications
Papers, talks, theses and reports from MOFOMO and from OcéanIA before it, newest first, each with its links and BibTeX.
2026 8 entries
Working document, version 0.1: Sanchez-Pi, N., & Martí, L. (2026). MOFOMO: Multimodal Ocean Foundation Models for an Ocean Digital Twin. Santiago, Saclay, Sophia Antipolis, Paris, Moorea: Inria – Institut national de recherche en sciences et technologies du numérique.
BibTeX
@book{mofomo-white-book-2026, title = {{MOFOMO}: Multimodal Ocean Foundation Models for an {O}cean Digital Twin}, author = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, publisher = {Inria -- Institut national de recherche en sciences et technologies du num\'{e}rique}, url = {https://mofomo.inria.cl}, month = sep, year = {2026}, note = {Working document, version 0.1}, address = {Santiago, Saclay, Sophia Antipolis, Paris, Moorea} }
Contreras Montanares, A. G., Valenzuela, L., Martí, L., & Sanchez-Pi, N. (2026). Planktonzilla: Multimodal dataset and models for understanding plankton ecosystems. Inria Chile Research Center.
BibTeX
@techreport{contrerasmontanares:hal-05621003, archiveprefix = {arXiv}, author = {Contreras Montanares, Alan Gerson and Valenzuela, Luis and Mart{\'i}, Luis and Sanchez-Pi, Nayat}, doi = {10.48550/arXiv.2606.00080}, eprint = {2606.00080}, eprinttype = {arxiv}, hal_id = {hal-05621003}, hal_version = {v1}, institution = {Inria Chile Research Center}, keywords = {Explainable AI; XAI ; Plankton Classification ; CLIPS ; Multimodal Classification}, month = may, primaryclass = {cs.CV}, title = {Planktonzilla: {M}ultimodal dataset and models for understanding plankton ecosystems}, url = {https://arxiv.org/abs/2606.00080}, year = {2026} }Valenzuela, L., Aguilera Madrid, S., Martí, L., & Sanchez-Pi, N. (2026). Benchmarking COX1 Embeddings across Genomic Foundation Models, kmers, and Imbalance-Aware Losses. In Fourteenth International Conference on Learning Representations (ICLR 2026) Workshop on Generative AI in Genomics (Gen2): Barriers and Frontiers.
BibTeX
@inproceedings{Valenzuela2026-wk, author = {Valenzuela, Luis and Aguilera Madrid, Sebastian and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {Fourteenth International Conference on Learning Representations (ICLR 2026) Workshop on Generative AI in Genomics (Gen\textsuperscript{2}): {B}arriers and Frontiers}, location = {Rio de Janeiro, Brazil}, month = may, title = {Benchmarking {COX1} Embeddings across Genomic Foundation Models, kmers, and Imbalance-Aware Losses}, url = {https://openreview.net/forum?id=9ywkije3Md}, year = {2026} }Valenzuela, L., Aguilera Madrid, S., Martí, L., & Sanchez-Pi, N. (2026). From k-mers to Genomic Foundation Models: Benchmarking COX1 Taxonomy under Extreme Class Imbalance. In Fourteenth International Conference on Learning Representations (ICLR 2026) Workshop on on Machine Learning for Genomics Explorations.
BibTeX
@inproceedings{valenzuela2026from, author = {Valenzuela, Luis and Aguilera Madrid, Sebasti{\'a}n and Mart{\'i}, Luis and Sanchez-Pi, Nayat}, booktitle = {Fourteenth International Conference on Learning Representations (ICLR 2026) Workshop on on Machine Learning for Genomics Explorations}, location = {Rio de Janeiro, Brazil}, month = may, title = {From k-mers to Genomic Foundation Models: {B}enchmarking {COX}1 Taxonomy under Extreme Class Imbalance}, url = {https://openreview.net/forum?id=NkROfzjt4g}, year = {2026} }Neto, M., Marquet, P., Freilich, M., Martí, L., & Sanchez-Pi, N. (2026). Beyond the Critical Depth: The Metabolic and Physical Drivers of Phytoplankton Persistence in a Changing Ocean.
BibTeX
@techreport{neto2026criticaldepthmetabolicphysical, archiveprefix = {arXiv}, author = {Neto, Mat\'{i}as and Marquet, Pablo and Freilich, Mara and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, doi = {10.48550/arXiv.2604.14759}, eprint = {2604.14759}, primaryclass = {math.DS}, title = {Beyond the Critical Depth: {T}he Metabolic and Physical Drivers of Phytoplankton Persistence in a Changing Ocean}, year = {2026} }Neto, M., Garay, N., Martí, L., & Sanchez-Pi, N. (2026). From Mean-Field Limits to Semiclassical Concentration: Global Convergence of the Canonical Evolutionary Strategy. Inria Chile Research Center.
BibTeX
@techreport{neto2026meanfieldlimitssemiclassicalconcentration, archiveprefix = {arXiv}, author = {Neto, Mat\'{i}as and Garay, Nicol\'{a}s and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, eprint = {2605.30371}, institution = {Inria Chile Research Center}, primaryclass = {cs.NE}, title = {From Mean-Field Limits to Semiclassical Concentration: {G}lobal Convergence of the Canonical Evolutionary Strategy}, url = {https://arxiv.org/abs/2605.30371}, year = {2026} }Lira, H., Martí, L., & Sanchez-Pi, N. (2026). Prior-Informed Symbolic Regression for Multiview Scientific Discovery. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 790–798). New York, NY, USA: Association for Computing Machinery.
BibTeX
@inproceedings{10.1145/3795095.3805119, address = {New York, NY, USA}, author = {Lira, Hernan and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference}, doi = {10.1145/3795095.3805119}, isbn = {9798400724879}, keywords = {symbolic regression, multiview learning, evolutionary computing}, location = {Centro Internacional de Convenciones CIC-ANDE, San Jose, Costa Rica}, numpages = {9}, pages = {790–798}, publisher = {Association for Computing Machinery}, series = {GECCO '26}, title = {Prior-Informed Symbolic Regression for Multiview Scientific Discovery}, year = {2026} }Lira, H., Martí, L., & Sanchez-Pi, N. (2026). Prior Coverage and Search Bias in Multiview Symbolic Regression. In D. Bucur, A. Della Cioppa, T. Hu, & E. Medvet (Eds.), 19th International Conference on Parallel Problem Solving From Nature (PPSN 2026). Trento, Italy: Springer.
BibTeX
@inproceedings{lira-2026:prior-coverage, address = {Trento, Italy}, author = {Lira, Hernan and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {19th {I}nternational {C}onference on {P}arallel {P}roblem {S}olving From {N}ature ({PPSN} 2026)}, doi = {10.1007/978-3-032-36229-2_12}, editor = {Bucur, Doina and Della Cioppa, Antonio and Hu, Ting and Medvet, Eric}, publisher = {Springer}, title = {Prior Coverage and Search Bias in Multiview Symbolic Regression}, year = {2026} }
2025 4 entries
Lira, H., de Wolff, T., Martí, L., & Sanchez-Pi, N. (2025). FairTrees: A Deep Learning Approach for Identifying Deforestation on Satellite Images. In Advances in Artificial Intelligence — IBERAMIA 2024: 18th Ibero-American Conference on AI (pp. 173–184). Berlin, Heidelberg: Springer-Verlag.
BibTeX
@inproceedings{10.1007/978-3-031-80366-6_15, address = {Berlin, Heidelberg}, author = {Lira, Hernan and de Wolff, Taco and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {Advances in Artificial Intelligence --- {IBERAMIA} 2024: 18th Ibero-American Conference on AI}, doi = {10.1007/978-3-031-80366-6_15}, isbn = {978-3-031-80365-9}, keywords = {Deforestation Monitoring, Image Segmentation, Satellite Imagery}, location = {Montevideo, Uruguay}, numpages = {12}, pages = {173--184}, publisher = {Springer-Verlag}, title = {{FairTrees}: {A} Deep Learning Approach for Identifying Deforestation on Satellite Images}, url = {https://doi.org/10.1007/978-3-031-80366-6_15}, year = {2025} }Valenzuela, L., Reyes, C., Martí, L., & Sanchez-Pi, N. (2025). A Comparative Analysis of Language Model Embeddings from Genes and Proteins involved in the Biological Carbon Pump. In C. Astudillo, K. Suchan, & S. A. Velastin (Eds.), IEEE 15th International Conference on Pattern Recognition Systems (ICPRS) (pp. 1–7).
BibTeX
@inproceedings{valenzuela-2025:icprs, author = {Valenzuela, Luis and Reyes, Camila and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {IEEE 15th International Conference on Pattern Recognition Systems (ICPRS)}, doi = {10.1109/ICPRS66293.2025.11302855}, editor = {Astudillo, Cesar and Suchan, Karol and Velastin, Sergio A.}, keywords = {Proteins;Analytical models;Translation;Accuracy;Annotations;Biological system modeling;Transformers;Bioinformatics;Biological information theory;Carbon;Large Language Models;genomics;proteins;Biological Carbon Pump;embeddings}, location = {Vi\~{n}a del Mar, Chile}, pages = {1--7}, title = {A Comparative Analysis of Language Model Embeddings from Genes and Proteins involved in the Biological Carbon Pump}, year = {2025} }Lira, H., Martí, L., & Sanchez-Pi, N. (2025). Spanish-Mapudungun Translation using Transfer Learning for Low-resource languages. In C. Astudillo, K. Suchan, & S. A. Velastin (Eds.), IEEE 15th International Conference on Pattern Recognition Systems (ICPRS) (pp. 1–7).
BibTeX
@inproceedings{lira-2025:icprs, author = {Lira, Hernan and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {IEEE 15th International Conference on Pattern Recognition Systems (ICPRS)}, doi = {10.1109/ICPRS66293.2025.11302844}, editor = {Astudillo, Cesar and Suchan, Karol and Velastin, Sergio A.}, keywords = {Training;South America;Vocabulary;Schedules;Translation;Transfer learning;Neural machine translation;Linguistics;Data models;Tokenization;neural machine translation;transfer learning;low-resource languages}, location = {Vi\~{n}a del Mar, Chile}, pages = {1--7}, title = {Spanish-{M}apudungun Translation using Transfer Learning for Low-resource languages}, year = {2025} }Chacra, E., Escapil-Inchauspé, P., Martí, L., & Sanchez-Pi, N. (2025). Physics-Informed Neural Networks for Coupled Fluid Dynamics and Nutrient Transport: A Comparative Study of Causal Training Methods. In C. Astudillo, K. Suchan, & S. A. Velastin (Eds.), IEEE 15th International Conference on Pattern Recognition Systems (ICPRS) (pp. 1–7).
BibTeX
@inproceedings{chacra-2025:icprs, author = {Chacra, Emir and Escapil-Inchausp\'{e}, Paul and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {IEEE 15th International Conference on Pattern Recognition Systems (ICPRS)}, doi = {10.1109/ICPRS66293.2025.11302850}, editor = {Astudillo, Cesar and Suchan, Karol and Velastin, Sergio A.}, keywords = {Training;Sensitivity;Biological system modeling;Fluid dynamics;Plankton;Neural networks;Nutrients;Throughput;Mathematical models;Stakeholders;physics-informed neural networks;nutrient transport modeling;multi-physics systems;causal training;scientific machine learning}, location = {Vi\~{n}a del Mar, Chile}, pages = {1-7}, title = {Physics-Informed Neural Networks for Coupled Fluid Dynamics and Nutrient Transport: {A} Comparative Study of Causal Training Methods}, year = {2025} }
2024 5 entries
Callejas, S., Lira, H., Berry, A., Martí, L., & Sanchez-Pi, N. (2024). Capturing the Essence of Plankton:A Gradient-Weighted Class Activation Mapping Analysis. In L. Correia, A. Rosá, & F. Garijo (Eds.), Advances in Artificial Intelligence — IBERAMIA 2024 (pp. 74–86). Cham: Springer Nature Switzerland.
BibTeX
@inproceedings{10.1007/978-3-031-80366-6_7, address = {Cham}, author = {Callejas, Sof\'{i}a and Lira, Hernan and Berry, Andrew and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {Advances in Artificial Intelligence --- IBERAMIA 2024}, doi = {10.1007/978-3-031-80366-6_7}, editor = {Correia, Lu{\'i}s and Ros{\'a}, Aiala and Garijo, Francisco}, isbn = {978-3-031-80366-6}, location = {Montevideo, Uruguay}, month = nov, pages = {74--86}, publisher = {Springer Nature Switzerland}, series = {Lecture Notes in Computer Science}, title = {Capturing the Essence of Plankton:{A} Gradient-Weighted Class Activation Mapping Analysis}, year = {2024} }Valenzuela, L. (2024, October). Inteligencia Artificial y Genómica para comprender los océanos y el cambio climático. Fête de la Science 2024 Chile.
BibTeX
@misc{lvalenzuela-2024--fete-de-la-science, author = {Valenzuela, Luis}, booktitle = {F{\^e}te de la Science 2024 Chile}, month = oct, title = {Inteligencia Artificial y Gen\'{o}mica para comprender los oc\'{e}anos y el cambio clim\'{a}tico}, year = {2024} }Callejas, S., Lira, H., Berry, A., Martí, L., & Sanchez-Pi, N. (2024). No Plankton Left Behind: Preliminary results on massive plankton image recognition. In G. Guerrero, S. Martín, E. Meneses, C. J. Barrios H, C. Osthoff, & J. M. Monsalve Diaz (Eds.), High Performance Computing: 11th Latin American High Performance Computing Conference (CARLA 2024).
BibTeX
@inproceedings{callejas-2024:carla, author = {Callejas, Sof\'{i}a and Lira, Hernan and Berry, Andrew and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {High Performance Computing: 11th Latin American High Performance Computing Conference ({CARLA} 2024)}, editor = {Guerrero, Gin\'{e}s and Mart\'{i}n, San and Meneses, Esteban and Barrios H, Carlos J and Osthoff, Carla and Monsalve Diaz, Jose M}, isbn = {978-3-031-80083-2}, issn = {1865-0929}, month = oct, series = {Communications in Computer and Information Science}, title = {No Plankton Left Behind: {P}reliminary results on massive plankton image recognition}, year = {2024} }Project presentation to students: Valenzuela, L. (2024, August). Descubriendo ecuaciones científicas mediante big data, genómica marina y machine learning. Seminario de Postgrado Magíster en Análisis Avanzado de Datos Multivariantes y Big Data. Santiago, Chile: Facultad de Ingeniería, Ciencia y Tecnología, Universidad Bernardo OHiggins.
BibTeX
@misc{lvalenzuela-2024--ubo, address = {Santiago, Chile}, author = {Valenzuela, Luis}, booktitle = {Seminario de Postgrado Mag\'{i}ster en An\'{a}lisis Avanzado de Datos Multivariantes y Big Data}, institution = {Facultad de Ingenier\'{i}a, Ciencia y Tecnolog\'{i}a, Universidad Bernardo OHiggins.}, month = aug, note = {Project presentation to students}, title = {Descubriendo ecuaciones cient\'{i}ficas mediante big data, gen\'{o}mica marina y machine learning}, year = {2024} }Martí, L. (2024, April). Modelos de Inteligencia Artificial aplicados a la comprensión de los océanos y cambio climático. Blue Talk: Los Océanos y el Desarrollo Sostenible: Retos, Tecnologías y Conservación, Chile. Pontificia Universidad Católica de Valparaíso.
BibTeX
@misc{lmarti-2024--blue-talk, author = {Mart\'{i}, Luis}, booktitle = {Blue Talk: Los Oc\'{e}anos y el Desarrollo Sostenible: Retos, Tecnolog\'{i}as y Conservaci\'{o}n, Chile}, institution = {Pontificia Universidad Cat\'{o}lica de Valpara\'{i}so}, location = {Valpara\'{i}so, Chile}, month = apr, title = {Modelos de Inteligencia Artificial aplicados a la comprensi\'{o}n de los oc\'{e}anos y cambio clim\'{a}tico}, year = {2024} }
2023 16 entries
Carrillo, H., de Wolff, T., Martí, L., & Sanchez-Pi, N. (2023). Evolutionary multi-objective physics-informed neural networks: The MOPINNs approach. AI Communications, 1–13.
BibTeX
@article{10.3233/aic-230073, author = {Carrillo, Hugo and de~Wolff, Taco and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, doi = {10.3233/aic-230073}, issn = {0921-7126}, journal = {AI Communications}, month = dec, pages = {1--13}, publisher = {IOS Press}, title = {Evolutionary multi-objective physics-informed neural networks: {T}he {MOPINN}s approach}, url = {http://dx.doi.org/10.3233/AIC-230073}, year = {2023} }Vasconcellos, E. C., Sampaio, R. M., Araújo, A. P. D., Gonzales Clua, E. W., Preux, P., Guerra, R., Gonçalves, L. M. G., Martí, L., Lira, H., & Sanchez-Pi, N. (2023). Reinforcement-learning robotic sailboats: Simulator and preliminary results. In NeurIPS 2023 Workshop on Robot Learning Workshop: Pretraining, Fine-Tuning, and Generalization with Large Scale Models. New Orleans, United States.
BibTeX
@inproceedings{vasconcellos:hal-04395990, address = {New Orleans, United States}, author = {Vasconcellos, Eduardo Charles and Sampaio, Ronald M and Ara{\'u}jo, Andr{\'e} P D and Gonzales Clua, Esteban Walter and Preux, Philippe and Guerra, Raphael and Gon{\c c}alves, Luiz M G and Mart{\'i}, Luis and Lira, Hernan and Sanchez-Pi, Nayat}, booktitle = {{NeurIPS 2023 Workshop on Robot Learning Workshop: Pretraining, Fine-Tuning, and Generalization with Large Scale Models}}, hal_id = {hal-04395990}, hal_version = {v1}, keywords = {artificial intelligence, reinforcement learning, unmanned surface vessel}, month = dec, pdf = {https://inria.hal.science/hal-04395990/file/neurips_wrl2023.pdf}, title = {Reinforcement-learning robotic sailboats: {S}imulator and preliminary results}, url = {https://inria.hal.science/hal-04395990}, year = {2023} }Keynote: Martí, L. (2023). Explainable AI for understanding plankton communities. In Journées scientifiques Inria Chile 2023.
BibTeX
@conference{lmarti-2023--jsic, author = {Mart\'{i}, Luis}, booktitle = {Journ\'{e}es scientifiques Inria Chile 2023}, location = {Santiago/Valpara\'{i}so/Concepci\'{o}n, Chile}, month = dec, note = {Keynote}, title = {Explainable {AI} for understanding plankton communities}, year = {2023} }Keynote: Martí, L. (2023). AI for (climate) good. In Escuela de Verano en Inteligencia Computacional. Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile.
BibTeX
@conference{lmarti-2023--evic, author = {Mart\'{i}, Luis}, booktitle = {Escuela de Verano en Inteligencia Computacional}, institution = {Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile}, location = {Santiago de Chile, Chile}, month = dec, note = {Keynote}, title = {{AI} for (climate) good}, year = {2023} }Valenzuela, L. (2023). Modeling global plankton communities via multinomics and ML approaches. In Journées scientifiques Inria Chile 2023.
BibTeX
@conference{valenzuela-2023--jsic, author = {Valenzuela, Luis}, booktitle = {Journ\'{e}es scientifiques Inria Chile 2023}, location = {Santiago/Valpara\'{i}so/Concepci\'{o}n, Chile}, month = dec, title = {Modeling global plankton communities via multinomics and ML approaches}, year = {2023} }Fierro Ulloa, J. I. (2023). NeuralODEs for phytoplankton modeling. In Journées scientifiques Inria Chile 2023.
BibTeX
@conference{fierro-2023--jsic, author = {Fierro Ulloa, Joel Ignacio}, booktitle = {Journ\'{e}es scientifiques Inria Chile 2023}, month = dec, title = {{NeuralODEs} for phytoplankton modeling}, year = {2023}, location = {Santiago/Valpara\'{i}so/Concepci\'{o}n, Chile} }Migus, L. (2023, December). Deep neural networks and partial differential equations (phdthesis). Sorbonne Université.
BibTeX
@thesis{migus:tel-04336969, title = {Deep neural networks and partial differential equations}, author = {Migus, L{\'e}on}, url = {https://theses.hal.science/tel-04336969}, number = {2023SORUS356}, institution = {Sorbonne Universit{\'e}}, supervisor = {Julien Salomnon and Patrick Gallinari}, year = {2023}, month = dec, keywords = {Deep neural networks ; Differential equations ; Numerical schemes ; Machine learning ; R{\'e}seaux de neurones ; Equations diff{\'e}rentielles ; Sch{\'e}mas num{\'e}riques ; Apprentissage machine}, type = {phdthesis}, pdf = {https://theses.hal.science/tel-04336969/file/MIGUS_Leon_these_2023.pdf}, hal_id = {tel-04336969}, hal_version = {v1} }Ferreira de Moraes, R., Evangelista, R. dos S., Pereira, A. L. da S., Toledo, Y. P., Fernandes, L. A. F., & Martí, L. (2023). Heuristics to reduce linear combinations of activation functions to improve image classification. In 2023 36th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 169–174). IEEE.
BibTeX
@inproceedings{10347043, author = {Ferreira de Moraes, Rog\'{e}rio and Evangelista, Raphael dos S. and Pereira, Andre Luiz da S. and Toledo, Yanexis Pupo and Fernandes, Leandro A. F. and Mart\'{i}, Luis}, booktitle = {2023 36th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)}, doi = {10.1109/SIBGRAPI59091.2023.10347043}, hal_id = {hal-04396390}, hal_version = {v1}, issn = {2377-5416}, keywords = {Training ; Graphics ; Computer vision ; Computational efficiency ; Convolutional neural networks ; Task analysis ; Image classification}, location = {Rio Grande, Brazil}, month = nov, number = {}, pages = {169--174}, publisher = {IEEE}, title = {Heuristics to reduce linear combinations of activation functions to improve image classification}, volume = {}, year = {2023} }Martí, L. (2023, October). AI for (climate) good. Seminar Series of the Institute of Astrophysics Studies, Universidad Diego Portales. Institute of Astrophysics Studies, Universidad Diego Portales.
BibTeX
@misc{lmarti-2023--udp, author = {Mart\'{i}, Luis}, booktitle = {Seminar Series of the Institute of Astrophysics Studies, Universidad Diego Portales}, institution = {Institute of Astrophysics Studies, Universidad Diego Portales}, location = {Santiago de Chile, Chile}, month = oct, title = {{AI} for (climate) good}, year = {2023} }Sanchez-Pi, N., & Martí, L. (2023). Opportunities in Chile: from the origin of the universe to the depths of the ocean. In Journées scientifiques Inria Chile 2023.
BibTeX
@conference{sanchez-pi-2023--jjss-inria, author = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, booktitle = {Journ\'{e}es scientifiques Inria Chile 2023}, location = {Inria Bordeaux, France}, month = sep, title = {Opportunities in {C}hile: from the origin of the universe to the depths of the ocean}, url = {https://mediatheque.inria.fr/Mediatheque/embed/public/79139}, year = {2023} }Valenzuela, L. (2023, September). Inteligencia Artificial y Genómica para comprender los océanos y el cambio climático. Fête de la Science 2023 Chile.
BibTeX
@misc{lvalenzuela-2023--fete-de-la-science, author = {Valenzuela, Luis}, booktitle = {F{\^e}te de la Science 2023 Chile}, month = sep, title = {Inteligencia Artificial y Gen\'{o}mica para comprender los oc\'{e}anos y el cambio clim\'{a}tico}, year = {2023} }Fierro Ulloa, J. I., & Bernard, O. (2023). Physic-informed neural networks for microalgae modeling. In ECCE 14 & ECAB 7 - 14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology. Berlin, Germany.
BibTeX
@inproceedings{bernard2023physic, title = {Physic-informed neural networks for microalgae modeling}, author = {Fierro Ulloa, Joel Ignacio and Bernard, Olivier}, url = {https://inria.hal.science/hal-04390804}, booktitle = {{ECCE} 14 \& {ECAB} 7 - 14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology}, address = {Berlin, Germany}, year = {2023}, month = sep, hal_id = {hal-04390804}, hal_version = {v1} }Carrillo, H. (2023). A Reduced Basis (RB) approach combined with Artificial Neural Networks (ANN) for optimal location of measurements for inverse problems in PDEs. In numhyp23: Numerical Methods for Hyperbolic Problems.
BibTeX
@conference{carrillo-2023--fr, author = {Carrillo, Hugo}, booktitle = {numhyp23: {N}umerical Methods for Hyperbolic Problems}, location = {Bordeaux, France}, month = jun, title = {A Reduced Basis ({RB}) approach combined with Artificial Neural Networks ({ANN}) for optimal location of measurements for inverse problems in PDEs}, url = {https://numhyp23.sciencesconf.org/}, year = {2023} }Keynote: Sanchez-Pi, N. (2023). AI, the Ocean and Climate Change. In KHIPU: Latin American Meeting on Artificial Intelligence.
BibTeX
@conference{sanchez-pi-2023--khipu, author = {Sanchez-Pi, Nayat}, booktitle = {KHIPU: Latin American Meeting on Artificial Intelligence}, location = {Universidad de La Rep\'{u}blica, Uruguay}, month = mar, note = {Keynote}, title = {{AI}, the Ocean and Climate Change}, url = {https://khipu.ai/khipu2023/}, year = {2023} }Ferreira de Moraes, R. (2023). Novas Abordagens para Função de Perda e Função de Ativação para Classificação de Imagens (phdthesis). Universidade Federal Fluminense.
BibTeX
@thesis{rogerio-phd, author = {Ferreira de Moraes, Rog\'{e}rio}, institution = {Universidade Federal Fluminense}, location = {Niterói, Brazil}, supervisor = {Leandro Fernandes and Luis Mart\'{i}}, title = {Novas Abordagens para Função de Perda e Função de Ativação para Classificação de Imagens}, type = {phdthesis}, year = {2023} }Project presentation to students: Valenzuela, L. (2023). OcéanIA. Santiago, Chile: Universidad Austral de Chile.
BibTeX
@misc{lvalenzuela-2023--uach, address = {Santiago, Chile}, author = {Valenzuela, Luis}, institution = {Universidad Austral de Chile}, note = {Project presentation to students}, title = {Oc\'{e}anIA}, year = {2023} }
2022 7 entries
de Wolff, T., Carrillo Lincopi, H., Sanchez-Pi, N., & Martí, L. (2022). MOPINNs: An Evolutionary Multi-Objective Approach to Physics-Informed Neural Networks. In Proceedings of The Genetic and Evolutionary Computation Conference 2022 (GECCO ’22). New York, NY, USA: Association for Computing Machinery.
BibTeX
@inproceedings{10.1145/3520304.3529071, address = {New York, NY, USA}, author = {de Wolff, Taco and Carrillo Lincopi, Hugo and Sanchez-Pi, Nayat and Mart\'{i}, Luis}, booktitle = {Proceedings of The Genetic and Evolutionary Computation Conference 2022 (GECCO '22)}, doi = {10.1145/3520304.3529071}, isbn = {781450392686}, location = {Boston, MA}, month = jul, numpages = {4}, publisher = {Association for Computing Machinery}, series = {GECCO'22}, title = {{MOPINNs}: {A}n Evolutionary Multi-Objective Approach to Physics-Informed Neural Networks}, url = {https://doi.org/10.1145/3520304.3529071}, year = {2022} }Sanchez-Pi, N., & Martí, L. (Eds.). (2022). AI: Modeling Oceans and Climate Change Workshop (AIMOCC 2022). Vienna, Austria: 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022).
BibTeX
@proceedings{sanchez-marti-2022:aimocc, address = {Vienna, Austria}, editor = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, month = jul, publisher = {31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022)}, title = {{AI: Modeling Oceans and Climate Change Workshop (AIMOCC 2022)}}, url = {https://oceania.inria.cl/#aimocc-2022}, year = {2022} }Carrillo, H., de Wolff, T., Martí, L., & Sanchez-Pi, N. (2022). Towards Optimally Weighted Physics-Informed Neural Networks in Ocean Modelling. In N. Sanchez-Pi & L. Martí (Eds.), Workshop AI: Modeling Oceans and Climate Change (AIMOCC 2022) of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022).
BibTeX
@inproceedings{hugo-vienna, author = {Carrillo, Hugo and de Wolff, Taco and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {Workshop AI: Modeling Oceans and Climate Change (AIMOCC 2022) of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022)}, editor = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, location = {Vienna, Austria}, month = jul, title = {Towards Optimally Weighted Physics-Informed Neural Networks in Ocean Modelling}, year = {2022} }Arroyo, J. I., Díez, B., Kempes, C. P., West, G. B., & Marquet, P. A. (2022). A general theory for temperature dependence in biology. Proceedings of the National Academy of Sciences of the United States of America, 119(30), e2119872119.
BibTeX
@article{Arroyo2022-fw, title = {A general theory for temperature dependence in biology}, author = {Arroyo, Jos{\'e} Ignacio and D{\'i}ez, Beatriz and Kempes, Christopher P and West, Geoffrey B and Marquet, Pablo A}, affiliation = {Departamento de Ecolog{\'\i}a, Facultad de Ciencias Biol{\'o}gicas, Pontificia Universidad Cat{\'o}lica de Chile, CP 8331150 Santiago, Chile. The Santa Fe Institute, Santa Fe, NM 87501. Departamento de Gen{\'e}tica Molecular y Microbiolog{\'\i}a, Facultad de Ciencias Biol{\'o}gicas, Pontificia Universidad Cat{\'o}lica de Chile, CP 8331150 Santiago, Chile. Center for Climate and Resilience Research, FONDAP (Fondo de Financiamiento de Centros de Investigaci{\'o}n en {\'A}reas Prioritarias), University of Chile, CP 8370449 Santiago, Chile. Center for Genome Regulation, FONDAP, Faculty of Science, University of Chile, CP 7800003 Santiago, Chile. Instituto de Ecolog{\'\i}a y Biodiversidad, CP 7800003 Santiago, Chile. Centro de Cambio Global Universidad Cat{\'o}lica, Facultad de Ciencias Biol{\'o}gicas, Pontificia Universidad Cat{\'o}lica de Chile, CP 8331150 Santiago, Chile. Instituto de Sistemas Complejos de Valpara{\'\i}so, CP 2340000 Valpara{\'\i}so, Chile. Centro de Modelamiento Matem{\'a}tico, Universidad de Chile, International Research Laboratory 2807, CNRS, CP 8370456 Santiago, Chile.}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {119}, number = {30}, pages = {e2119872119}, month = jul, year = {2022}, url = {http://dx.doi.org/10.1073/pnas.2119872119}, keywords = {metabolic theory; scaling; temperature kinetics}, language = {en}, issn = {0027-8424, 1091-6490}, pmid = {35858416}, doi = {10.1073/pnas.2119872119}, pmc = {PMC9335213} }Aguayo, J., & Lincopi, H. C. (2022). Analysis of Obstacles Immersed in Viscous Fluids Using Brinkman’s Law for Steady Stokes and Navier-Stokes Equations. SIAM Journal Applied Mathematics, 82(4), 1369–1386.
BibTeX
@article{10.1137/20M138569X, address = {USA}, author = {Aguayo, Jorge and Lincopi, Hugo Carrillo}, doi = {10.1137/20M138569X}, issn = {0036-1399}, issue_date = {January 2022}, journal = {SIAM Journal Applied Mathematics}, keywords = {Stokes problem, Navier-Stokes, obstacles, penalization, Brinkman's law, 35, 65, 76}, month = jan, number = {4}, numpages = {18}, pages = {1369--1386}, publisher = {Society for Industrial and Applied Mathematics}, title = {Analysis of Obstacles Immersed in Viscous Fluids Using Brinkman's Law for Steady Stokes and Navier-Stokes Equations}, url = {https://doi.org/10.1137/20M138569X}, volume = {82}, year = {2022} }Lira, H., Martí, L., & Sanchez-Pi, N. (2022). A Graph Neural Network with Spatio-Temporal Attention for Multi-Sources Time Series Data: An Application to Frost Forecast. Sensors, 22(4).
BibTeX
@article{lira-2022:graph-nn-frost, article-number = {1486}, author = {Lira, Hernan and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, doi = {10.3390/s22041486}, hal_id = {hal-03541565}, hal_version = {v1}, issn = {1424-8220}, journal = {Sensors}, number = {4}, title = {A Graph Neural Network with Spatio-Temporal Attention for Multi-Sources Time Series Data: {A}n Application to Frost Forecast}, url = {https://www.mdpi.com/1424-8220/22/4/1486}, volume = {22}, year = {2022} }de Wolff, T., Carrillo, H., Martí, L., & Sanchez-Pi, N. (2022). Optimal Architecture Discovery for Physics-Informed Neural Networks. In A. C. Bicharra Garcia, M. Ferro, & J. C. Rodríguez Ribón (Eds.), Advances in Artificial Intelligence — IBERAMIA 2022 (pp. 77–88). Cham: Springer International Publishing.
BibTeX
@inproceedings{10.1007/978-3-031-22419-5_7, address = {Cham}, author = {de Wolff, Taco and Carrillo, Hugo and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {Advances in Artificial Intelligence --- {IBERAMIA} 2022}, doi = {10.1007/978-3-031-22419-5_7}, editor = {Bicharra Garcia, Ana Cristina and Ferro, Mariza and Rodr\'{i}guez Rib\'{o}n, Julio Cesar}, isbn = {978-3-031-22419-5}, pages = {77--88}, publisher = {Springer International Publishing}, title = {Optimal Architecture Discovery for Physics-Informed Neural Networks}, year = {2022} }
2021 9 entries
Ferreira de Moraes, R., Evangelista, R. dos S., Fernandes, L. A. F., & Martí, L. (2021). GCOOD: A Generic Coupled Out-of-Distribution Detector for Robust Classification. In 2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 409–416).
BibTeX
@inproceedings{9643095, author = {Ferreira de Moraes, Rog\'{e}rio and Evangelista, Raphael dos S. and Fernandes, Leandro A. F. and Mart\'{i}, Luis}, booktitle = {2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)}, doi = {10.1109/SIBGRAPI54419.2021.00062}, hal_id = {hal-04396403}, hal_version = {v1}, issn = {2377-5416}, keywords = {Training ; Graphics ; Neural networks ; Detectors ; Convolutional neural networks ; Task analysis ; Faces}, location = {Gramado, Rio Grande do Sul, Brazil}, month = oct, number = {}, pages = {409--416}, title = {{GCOOD}: {A} Generic Coupled Out-of-Distribution Detector for Robust Classification}, volume = {}, year = {2021} }Invited tutorial: Sanchez-Pi, N., & Martí, L. (2021). Towards a Green AI: Evolutionary Solutions for an Ecologically Viable Artificial Intelligence. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1135–1140). New York, NY, USA: Association for Computing Machinery.
BibTeX
@conference{10.1145/3449726.3461428, address = {New York, NY, USA}, author = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference Companion}, doi = {10.1145/3449726.3461428}, isbn = {9781450383516}, location = {Lille, France}, month = jul, note = {Invited tutorial}, numpages = {6}, pages = {1135--1140}, publisher = {Association for Computing Machinery}, series = {GECCO'21}, title = {Towards a Green {AI}: {E}volutionary Solutions for an Ecologically Viable Artificial Intelligence}, url = {https://doi.org/10.1145/3449726.3461428}, year = {2021} }The OcénIA Project White Book: Sanchez-Pi, N., Martí, L., Abreu, A., Bernard, O., de Vargas, C., Eveillard, D., Maass, A., Marquet, P. A., Sainte-Marie, J., Salomon, J., Schoenauer, M., & Sebag, M. (2021). OcéanIA: AI, Data, and Models for Understanding the Ocean and Climate Change. (N. Sanchez-Pi & L. Martí, Eds.). Lille, Paris, Saclay, Santiago, Sophia-Antipolis: Inria – Institut national de recherche en sciences et technologies du numérique.
BibTeX
@book{oceania-white-book-2021, address = {Lille, Paris, Saclay, Santiago, Sophia-Antipolis}, author = {Sanchez-Pi, Nayat and Mart\'{i}, Luis and Abreu, Andr\'{e} and Bernard, Olivier and de~Vargas, Colomban and Eveillard, Damien and Maass, Alejandro and Marquet, Pablo~A. and Sainte-Marie, Jacques and Salomon, Julien and Schoenauer, Marc and Sebag, Mich\`{e}le}, editor = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, eprint = {hal-01882235}, eprinttype = {hal}, hal_id = {hal-03274323}, hal_version = {v1}, month = jul, note = {The Oc\'{e}nIA Project White Book}, publisher = {Inria -- Institut national de recherche en sciences et technologies du num\'{e}rique}, title = {{Oc\'{e}anIA}: {AI}, Data, and Models for Understanding the Ocean and Climate Change}, url = {http://oceania.inria.cl}, year = {2021} }Sanchez-Pi, N., & Martí, L. (Eds.). (2021). AI: Modeling Oceans and Climate Change Workshop (AIMOCC 2021). Santiago de Chile (Virtual): Tenth International Conference on Learning Representations (ICLR 2021).
BibTeX
@proceedings{sanchez-marti-2021:aimocc, address = {Santiago de Chile (Virtual)}, editor = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, month = may, publisher = {Tenth International Conference on Learning Representations (ICLR 2021)}, title = {{AI: Modeling Oceans and Climate Change Workshop (AIMOCC 2021)}}, url = {https://oceania.inria.cl/#aimocc}, year = {2021} }Lira, H., Martí, L., & Sanchez-Pi, N. (2021). Frost forecasting model using graph neural networks with spatio-temporal attention. In N. Sanchez-Pi & L. Martí (Eds.), AI: Modeling Oceans and Climate Change Workshop at ICLR 2021. Santiago, Chile.
BibTeX
@inproceedings{lira:hal-03259658, address = {Santiago, Chile}, author = {Lira, Hernan and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {AI: Modeling Oceans and Climate Change Workshop at ICLR 2021}, editor = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, hal_id = {hal-03259658}, hal_version = {v1}, month = may, pdf = {https://hal.inria.fr/hal-03259658/file/iclr2021_conference.pdf}, title = {Frost forecasting model using graph neural networks with spatio-temporal attention}, url = {https://hal.inria.fr/hal-03259658}, year = {2021} }de Wolff, T., Carrillo, H., Martí, L., & Sanchez-Pi, N. (2021, May). Towards Optimally Weighted Physics-Informed Neural Networks in Ocean Modelling.
BibTeX
@unpublished{dewolff:hal-03260357, archiveprefix = {arXiv}, author = {de Wolff, Taco and Carrillo, Hugo and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, eprint = {2106.08747}, hal_id = {hal-03260357}, hal_version = {v1}, month = may, pdf = {https://hal.inria.fr/hal-03260357/file/neurips_neural-based_solver.pdf}, primaryclass = {physics.ao-ph}, title = {Towards Optimally Weighted Physics-Informed Neural Networks in Ocean Modelling}, url = {https://hal.inria.fr/hal-03260357}, year = {2021} }de Wolff, T., Carrillo, H., Martí, L., & Sanchez-Pi, N. (2021). Assessing Physics Informed Neural Networks in Ocean Modelling and Climate Change Applications. In N. Sanchez-Pi & L. Martí (Eds.), AI: Modeling Oceans and Climate Change Workshop at ICLR 2021. Santiago (Virtual), Chile.
BibTeX
@inproceedings{dewolff:hal-03262684, address = {Santiago (Virtual), Chile}, author = {de Wolff, Taco and Carrillo, Hugo and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {{AI}: {M}odeling Oceans and Climate Change Workshop at {ICLR} 2021}, editor = {Sanchez-Pi, Nayat and Mart\'{i}, Luis}, hal_id = {hal-03262684}, hal_version = {v1}, month = may, pdf = {https://hal.inria.fr/hal-03262684/file/iclr2021_conference.pdf}, title = {Assessing Physics Informed Neural Networks in Ocean Modelling and Climate Change Applications}, url = {https://hal.inria.fr/hal-03262684}, year = {2021} }Demory, D., Weitz, J. S., Baudoux, A.-C., Touzeau, S., Simon, N., Rabouille, S., Sciandra, A., & Bernard, O. (2021). A thermal trade-off between viral production and degradation drives virus-phytoplankton population dynamics. Ecology Letters, 24(6), 1133–1144.
BibTeX
@article{demory-2021--thermal-trade-off, author = {Demory, David and Weitz, Joshua S. and Baudoux, Anne-Claire and Touzeau, Suzanne and Simon, Natalie and Rabouille, Sophie and Sciandra, Antoine and Bernard, Olivier}, doi = {10.1111/ele.13722}, editor = {Lafferty, Kevin}, journal = {Ecology Letters}, month = apr, number = {6}, pages = {1133--1144}, publisher = {Wiley}, title = {A thermal trade-off between viral production and degradation drives virus-phytoplankton population dynamics}, url = {https://doi.org/10.1111/ele.13722}, volume = {24}, year = {2021} }Muñoz, A., Martí, L., & Sanchez-Pi, N. (2021). Data Governance, a Knowledge Model Through Ontologies. In R. Valencia-García, M. Bucaram-Leverone, J. Del Cioppo-Morstadt, N. Vera-Lucio, & E. Jácome-Murillo (Eds.), Technologies and Innovation (pp. 18–32). Cham: Springer International Publishing.
BibTeX
@inproceedings{10.1007/978-3-030-88262-4_2, address = {Cham}, author = {Mu\~{n}oz, Ana and Mart\'{i}, Luis and Sanchez-Pi, Nayat}, booktitle = {Technologies and Innovation}, doi = {10.1007/978-3-030-88262-4_2}, editor = {Valencia-Garc\'{i}a, Rafael and Bucaram-Leverone, Martha and Del Cioppo-Morstadt, Javier and Vera-Lucio, N\'{e}stor and J\'{a}come-Murillo, Emma}, isbn = {978-3-030-88262-4}, issn = {1865-0929}, pages = {18--32}, publisher = {Springer International Publishing}, title = {Data Governance, a Knowledge Model Through Ontologies}, year = {2021} }
2020 2 entries
Keynote: Sanchez-Pi, N. (2020). OcéanIA: AI, Oceans and Climate Change. In A. Ruiz-Garcia, I. Arraut, J. M. Banda, I. Lopez-Francos, F. Latorre, P. Magalhães Braga, K. Caballero Barajas, S. H. Garrido Mejia, E. U. Moya-Sánchez, V. Fernandes Caridá, C. Miranda, G. Bejarano, & J. Ortega Caro (Eds.), LatinX in AI (LXAI) workshop at NeurIPS 2020.
BibTeX
@conference{sanchez-pi-2020--latinxs-neurips, author = {Sanchez-Pi, Nayat}, booktitle = {LatinX in AI (LXAI) workshop at NeurIPS 2020}, editor = {Ruiz-Garcia, Ariel and Arraut, Ivan and Banda, Juan~M. and Lopez-Francos, Ignacio and Latorre, Fabian and Magalh\~{a}es Braga, Pedro and Caballero Barajas, Karla and Garrido Mejia, Sergio Hernan and Moya-S\'{a}nchez, Eduardo Ulises and Fernandes Carid\'{a}, Vinicius and Miranda, Carlos and Bejarano, Gissella and Ortega Caro, Josu\'{e}}, month = dec, note = {Keynote}, online_presentation_url = {https://slideslive.com/38942447/ai-oceans-and-climate-change}, title = {{Oc\'{e}anIA}: {AI}, Oceans and Climate Change}, url = {https://www.latinxinai.org/neurips-2020-about}, year = {2020} }Sanchez-Pi, N., Martí, L., Abreu, A., Bernard, O., de Vargas, C., Eveillard, D., Maass, A., Marquet, P. A., Sainte-Marie, J., Salomon, J., Schoenauer, M., & Sebag, M. (2020). Artificial Intelligence, Machine Learning and Modeling for Understanding the Oceans and Climate Change. In D. Dao, E. Sherwin, P. Donti, L. Kaack, L. Kuntz, Y. Yusuf, D. Rolnick, C. Nakalembe, C. Monteleoni, & Y. Bengio (Eds.), Tackling Climate Change with Machine Learning workshop at NeurIPS 2020.
BibTeX
@inproceedings{sanchez-pi-et-al-2020--neurips, author = {Sanchez-Pi, Nayat and Mart\'{i}, Luis and Abreu, Andr\'{e} and Bernard, Olivier and de~Vargas, Colomban and Eveillard, Damien and Maass, Alejandro and Marquet, Pablo~A. and Sainte-Marie, Jacques and Salomon, Julien and Schoenauer, Marc and Sebag, Mich\`{e}le}, booktitle = {Tackling Climate Change with Machine Learning workshop at NeurIPS 2020}, editor = {Dao, David and Sherwin, Evan and Donti, Priya and Kaack, Lynn and Kuntz, Lauren and Yusuf, Yumna and Rolnick, David and Nakalembe, Catherine and Monteleoni, Claire and Bengio, Yoshua}, hal_id = {hal-03138712}, hal_version = {v1}, month = dec, pdf = {https://hal.archives-ouvertes.fr/hal-03138712/file/paper.pdf}, slides_pdf_url = {https://www.climatechange.ai/papers/neurips2020/93/slides.pdf}, title = {Artificial Intelligence, Machine Learning and Modeling for Understanding the Oceans and Climate Change}, url = {https://www.climatechange.ai/papers/neurips2020/93}, year = {2020} }
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