Gradient-based Planning with World Models

no code implementations • 28 Dec 2023 • Jyothir S V, Siddhartha Jalagam, Yann Lecun, Vlad Sobal

The enduring challenge in the field of artificial intelligence has been the control of systems to achieve desired behaviours.

Model Predictive Control

A Cookbook of Self-Supervised Learning

no code implementations • 24 Apr 2023 • Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Gregoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann Lecun, Micah Goldblum

Self-supervised learning, dubbed the dark matter of intelligence, is a promising path to advance machine learning.

Navigate Self-Supervised Learning

Joint Embedding Predictive Architectures Focus on Slow Features

1 code implementation • 20 Nov 2022 • Vlad Sobal, Jyothir S V, Siddhartha Jalagam, Nicolas Carion, Kyunghyun Cho, Yann Lecun

Many common methods for learning a world model for pixel-based environments use generative architectures trained with pixel-level reconstruction objectives.

Light-weight probing of unsupervised representations for Reinforcement Learning

1 code implementation • 25 Aug 2022 • Wancong Zhang, Anthony GX-Chen, Vlad Sobal, Yann Lecun, Nicolas Carion

Unsupervised visual representation learning offers the opportunity to leverage large corpora of unlabeled trajectories to form useful visual representations, which can benefit the training of reinforcement learning (RL) algorithms.

reinforcement-learning Reinforcement Learning (RL) +2