Alex Hernández-García

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 31

Top Topics

Image Understanding

Multiagent Evolutionary Algorithm

Machine Learning

Top Venues

Publications

Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio
Multi-Fidelity Active Learning with GFlowNets. Trans. Mach. Learn. Res. 2024 (2024)
Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling. CoRR (2023)
Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin
A theory of continuous generative flow networks. CoRR (2023)
Alvaro Carbonero, Alexandre Duval, Victor Schmidt, Santiago Miret, Alex Hernández-García, Yoshua Bengio, David Rolnick
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions. CoRR (2023)
Moksh Jain, Tristan Deleu, Jason Hartford, Cheng-Hao Liu, Alex Hernández-García, Yoshua Bengio
GFlowNets for AI-Driven Scientific Discovery. CoRR (2023)
Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin
A theory of continuous generative flow networks. ICML (2023)
Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
FAENet: Frame Averaging Equivariant GNN for Materials Modeling. CoRR (2023)
Alexandra Volokhova, Michal Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca A. Thiede, Zichao Yan, Alán Aspuru-Guzik, Yoshua Bengio
Towards equilibrium molecular conformation generation with GFlowNets. CoRR (2023)
Jose González-Abad, Alex Hernández-García, Paula Harder, David Rolnick, José Manuel Gutiérrez Llorente
Multi-variable Hard Physical Constraints for Climate Model Downscaling. CoRR (2023)
Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio
Multi-Objective GFlowNets. ICML (2023)
Alex Hernández-García, Alexandre Duval, Alexandra Volokhova, Yoshua Bengio, Divya Sharma, Pierre Luc Carrier, Michal Koziarski, Victor Schmidt
Crystal-GFN: sampling crystals with desirable properties and constraints. CoRR (2023)
Alexandra Sasha Luccioni, Alex Hernández-García
Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning. CoRR (2023)
Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
FAENet: Frame Averaging Equivariant GNN for Materials Modeling. ICML (2023)
Victor Schmidt, Alexandra Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud, Sunand Raghupathi, Gautier Cosne, Adrien Juraver, Vahe Vardanyan, Alex Hernández-García, Yoshua Bengio
ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods. ICLR (2022)
Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
Biological Sequence Design with GFlowNets. ICML (2022)
Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design. CoRR (2022)
Paula Harder, Qidong Yang, Venkatesh Ramesh, Prasanna Sattigeri, Alex Hernández-García, Campbell D. Watson, Daniela Szwarcman, David S. Rolnick
Generating physically-consistent high-resolution climate data with hard-constrained neural networks. CoRR (2022)
Siba Moussa, Michael Kilgour, Clara Jans, Alex Hernández-García, Miroslava Cuperlovic-Culf, Yoshua Bengio, Lena Simine
Diversifying Design of Nucleic Acid Aptamers Using Unsupervised Machine Learning. CoRR (2022)
Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
Biological Sequence Design with GFlowNets. CoRR (2022)
Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio
Multi-Objective GFlowNets. CoRR (2022)
Samuel Albanie, João F. Henriques, Luca Bertinetto, Alex Hernández-García, Hazel Doughty, Gül Varol
Preface. Pre-Registration Workshop @ NeurIPS (2021)
Victor Schmidt, Alexandra Sasha Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud, Sunand Raghupathi, Gautier Cosne, Adrien Juraver, Vahe Vardanyan, Alex Hernández-García, Yoshua Bengio
ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods. CoRR (2021)
Alex Hernández-García
Rethinking supervised learning: insights from biological learning and from calling it by its name. CoRR (2020)
Alex Hernández-García
Data augmentation and image understanding. CoRR (2020)
Alex Hernández-García, Peter König
Learning Representational Invariance Instead of Categorization. ICCV Workshops (2019)
Alex Hernández-García, Peter König
Further advantages of data augmentation on convolutional neural networks. CoRR (2019)
Alex Hernández-García, Peter König, Tim C. Kietzmann
Learning robust visual representations using data augmentation invariance. CoRR (2019)
Alex Hernández-García, Peter König
Do deep nets really need weight decay and dropout? CoRR (2018)
Alex Hernández-García, Peter König
Data augmentation instead of explicit regularization. CoRR (2018)
Alex Hernández-García, Peter König
Further Advantages of Data Augmentation on Convolutional Neural Networks. ICANN (1) (2018)
Alex Hernández-García
Perceived emotion from images through deep neural networks. ACII (2017)