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ORCIDVlad Sobal
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2020 – today
- 2024
[i7]Nicklas Hansen, Jyothir S. V, Vlad Sobal, Yann LeCun, Xiaolong Wang, Hao Su:
Hierarchical World Models as Visual Whole-Body Humanoid Controllers. CoRR abs/2405.18418 (2024)- [i6]Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun:
𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. CoRR abs/2407.18134 (2024) - 2023
- [i5]Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum:
A Cookbook of Self-Supervised Learning. CoRR abs/2304.12210 (2023) - [i4]Jyothir S. V, Siddhartha Jalagam, Yann LeCun, Vlad Sobal:
Gradient-based Planning with World Models. CoRR abs/2312.17227 (2023) - 2022
- [i3]Vlad Sobal, Alfredo Canziani, Nicolas Carion, Kyunghyun Cho, Yann LeCun:
Separating the World and Ego Models for Self-Driving. CoRR abs/2204.07184 (2022) - [i2]Wancong Zhang, Anthony GX-Chen, Vlad Sobal, Yann LeCun, Nicolas Carion:
Light-weight probing of unsupervised representations for Reinforcement Learning. CoRR abs/2208.12345 (2022) - [i1]Vlad Sobal, Jyothir S. V, Siddhartha Jalagam, Nicolas Carion, Kyunghyun Cho, Yann LeCun:
Joint Embedding Predictive Architectures Focus on Slow Features. CoRR abs/2211.10831 (2022)
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