"Self-Imitation Learning," Oh and Guo et al.: arxiv.org/abs/1806.05635 Imitating past good experiences in the replay buffer leads to big improvements over A2C, PPO, inc. good Montezuma performance in fewer frames than prior approaches

Excited to share a quite extensive introduction to deep reinforcement learning! With ... Riashat Islam Marc G. Bellemare and Joelle Pineau, we hope it will be useful to the community. Print version available at #NeurIPS! arxiv.org/abs/1811.12560

Delighted to welcome reinforcement learning pioneer Satinder Singh to DeepMindAI. He’ll bring some incredible experience to the team and I'm really looking forward to working with him!

Join us and Blizzard Entertainment this Thursday at 6:00pm GMT for an exciting #StarCraft demonstration, hosted by Dan Stemkoski and Kevin van der Kooi 🇺🇦! Livestream on YouTube: youtube.com/c/deepmind Read more about #StarCraft2 as an environment for AI research: deepmind.com/blog/deepmind-…

really happy to announce the next version of our #RL framework: Dopamine 2.0! beyond atari: now we support general discrete-domain gym environments. we've been using this internally for our research and it allows us to test out new ideas very quickly. try it out!

CfP for the @ICLR2019 workshop on structure and priors in reinforcement learning (SPiRL), deadline 3/7! spirl.info/2019/call/

In a major scientific breakthrough, the latest version of #AlphaFold has been recognised as a solution to one of biology's grand challenges - the “protein folding problem”. It was validated today at #CASP14, the biennial Critical Assessment of protein Structure Prediction (1/3)

Our most recent work is out in Nature! We're reporting on (reinforcement) learning to navigate Loon stratospheric balloons and minimizing the sim2real gap. Results from a 39-day Pacific Ocean experiment show RL keeps its strong lead in real conditions. nature.com/articles/s4158…

I will be briefly talking about how I used JAX to implement my recent #NeurIPS2020 work on Discovering RL Algorithms (arxiv.org/pdf/2007.08794…). Stop by our livestream if you are interested. :)

Excited to share our new paper, "DataRater: Meta-Learned Dataset Curation"! We explore a fundamental question: How can we *automatically* learn which data is most valuable for training foundation models? Paper: arxiv.org/pdf/2505.17895 to appear NeurIPS Conference Thread 👇

@albert_swart Thank you for mentioning my code. :) They will merge Jeff Donahue's code soon. See the following PR: github.com/BVLC/caffe/pul…

Check out the code (with trained models) for our ICLR 2017 paper on video prediction. github.com/rubenvillegas/…

NIPS Deep RL Symposium deadline Fri Nov 3. We welcome your #ICLR Deep RL submissions! (+other recent work) sites.google.com/view/deeprl-sy…

NIPS Deep RL Symposium Schedule now available: sites.google.com/view/deeprl-sy… includes over 70 contributed papers/posters, and invited talks by David Silver, Joelle Pineau, Ruslan Russ Salakhutdinov , Ben Van Roy, Michael Bowling. Thursday 12/7 Ronny MacIntoshes Plus Jr 🐀