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Alex Hernández-García
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2020 – today
- 2024
- [j3]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. J. Mach. Learn. Res. 25: 106:1-106:26 (2024) - [j2]Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio:
Multi-Fidelity Active Learning with GFlowNets. Trans. Mach. Learn. Res. 2024 (2024) - [i23]Hyeonah Kim, Minsu Kim, Taeyoung Yun, Sanghyeok Choi, Emmanuel Bengio, Alex Hernández-García, Jinkyoo Park:
Improved Off-policy Reinforcement Learning in Biological Sequence Design. CoRR abs/2410.04461 (2024) - 2023
- [j1]Paula Harder, Alex Hernández-García, Venkatesh Ramesh, Qidong Yang, Prasanna Sattegeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick:
Hard-Constrained Deep Learning for Climate Downscaling. J. Mach. Learn. Res. 24: 365:1-365:40 (2023) - [c9]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: 9013-9033 - [c8]Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio:
Multi-Objective GFlowNets. ICML 2023: 14631-14653 - [c7]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: 18269-18300 - [i22]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 abs/2301.12594 (2023) - [i21]Moksh Jain, Tristan Deleu, Jason S. Hartford, Cheng-Hao Liu, Alex Hernández-García, Yoshua Bengio:
GFlowNets for AI-Driven Scientific Discovery. CoRR abs/2302.00615 (2023) - [i20]Alexandra Sasha Luccioni, Alex Hernández-García:
Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning. CoRR abs/2302.08476 (2023) - [i19]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 abs/2305.05577 (2023) - [i18]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 abs/2305.14452 (2023) - [i17]Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio:
Multi-Fidelity Active Learning with GFlowNets. CoRR abs/2306.11715 (2023) - [i16]Jose González-Abad, Alex Hernández-García, Paula Harder, David Rolnick, José Manuel Gutiérrez Llorente:
Multi-variable Hard Physical Constraints for Climate Model Downscaling. CoRR abs/2308.01868 (2023) - [i15]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 abs/2310.04925 (2023) - [i14]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 abs/2310.06682 (2023) - [i13]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 abs/2310.14782 (2023) - 2022
- [c6]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 - [c5]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: 9786-9801 - [i12]Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour
Biological Sequence Design with GFlowNets. CoRR abs/2203.04115 (2022) - [i11]Siba Moussa
Diversifying Design of Nucleic Acid Aptamers Using Unsupervised Machine Learning. CoRR abs/2208.05341 (2022) - [i10]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 abs/2208.05424 (2022) - [i9]Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio:
Multi-Objective GFlowNets. CoRR abs/2210.12765 (2022) - [i8]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 abs/2211.12020 (2022) - 2021
- [c4]Samuel Albanie, João F. Henriques, Luca Bertinetto, Alex Hernández-García, Hazel Doughty, Gül Varol:
Preface. Pre-Registration Workshop @ NeurIPS 2021: i - [e1]Samuel Albanie, João F. Henriques, Luca Bertinetto, Alex Hernández-García, Hazel Doughty, Gül Varol:
NeurIPS 2021 Workshop on Pre-Registration in Machine Learning, 13 December 2021, Virtual. Proceedings of Machine Learning Research 181, PMLR 2021 [contents] - [i7]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 abs/2110.02871 (2021) - 2020
- [b1]Alex Hernández-García:
Data augmentation and image understanding. University of Osnabrück, Germany, 2020, pp. 1-120 - [i6]Alex Hernández-García:
Rethinking supervised learning: insights from biological learning and from calling it by its name. CoRR abs/2012.02526 (2020) - [i5]Alex Hernández-García:
Data augmentation and image understanding. CoRR abs/2012.14185 (2020)
2010 – 2019
- 2019
- [c3]Alex Hernández-García, Peter König:
Learning Representational Invariance Instead of Categorization. ICCV Workshops 2019: 4587-4590 - [i4]Alex Hernández-García
Learning robust visual representations using data augmentation invariance. CoRR abs/1906.04547 (2019) - [i3]Alex Hernández-García
Further advantages of data augmentation on convolutional neural networks. CoRR abs/1906.11052 (2019) - 2018
- [c2]Alex Hernández-García
Further Advantages of Data Augmentation on Convolutional Neural Networks. ICANN (1) 2018: 95-103 - [i2]Alex Hernández-García
Do deep nets really need weight decay and dropout? CoRR abs/1802.07042 (2018) - [i1]Alex Hernández-García
Data augmentation instead of explicit regularization. CoRR abs/1806.03852 (2018) - 2017
- [c1]Alex Hernández-García:
Perceived emotion from images through deep neural networks. ACII 2017: 566-570
Coauthor Index
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