@rob_fergus

Director, AI Research and Head of FAIR at Meta

Joined January 2020
  • Tweets8
  • Following59
  • Followers3.5K
1/ Excited to share that I’m taking on the role of leading Fundamental AI Research (FAIR) at Meta. Huge thanks to Joelle for everything. Look forward to working closely again with Yann & team.
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2/ Meta's commitment to FAIR & research is unwavering. We're working towards building human-level experiences that transform technology & are dedicated to advancing AI research.
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Replying to @ylecun
@ylecun @AravSrinivas recent Proto-RL (arxiv.org/pdf/2102.11271.pdf) that uses ideas from both CURL and DrQ gets us closer to the LeCake, as it's contrastively learned representations are **fully detached** from RL, besides they can be learned with just the MaxEnt objective.
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Happy to share my new work -- Proto-RL, a task-agnostic pre-training scheme that reconciles exploration and representation learning in image-based RL! with: @rob_fergus, Alessandro Lazaric, and @LerrelPinto. paper: arxiv.org/pdf/2102.11271.pdf code: github.com/denisyarats/proto [1/N]
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Rob Fergus retweeted
Joshua Meier
@joshim52 Sep 2020
Excited to share an update to our work on evolutionary-scale modeling (ESM)! Over the past year, we rewrote our paper with better pretraining and downstream models, leading to state-of-the-art results across multiple benchmarks. (1/8) biorxiv.org/content/10.1101/…
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Excited to share our new paper “Automatic Data Augmentation for Generalization in Deep Reinforcement Learning” w/ @maxagoldstein8, @denisyarats, @ikostrikov, and @rob_fergus! Paper: arxiv.org/pdf/2006.12862.pdf Code: github.com/rraileanu/auto-dr… Website: sites.google.com/view/ucb-dr…
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Great work from my PhD students @denisyarats and @ikostrikov !
Denis Yarats
@denisyarats29 Apr 2020
Exciting to announce our new work together with @ikostrikov and @rob_fergus: Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. Paper: arxiv.org/abs/2004.13649 Code: github.com/denisyarats/drq Website: sites.google.com/view/data-r… [1/N]

Image Augmentation Is All You Need: Regularizing Deep...

We propose a simple data augmentation technique that can be applied to standard model-free reinforcement learning algorithms, enabling robust learning directly from pixels without the need for...

arxiv.org
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