Igor Mordatch

Optimization & Training · arXiv.org · 2021–2025

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Igor Mordatch trusts

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Paul J. Werbos (in Optimization & Training)

Papers from Igor Mordatch's perspective

Ordered by how strongly the researchers Igor Mordatch trusts endorse each paper. Same corpus, a different order for every researcher.

  1. MuJoCo: A physics engine for model-based control
  2. Proximal Policy Optimization Algorithms (arXiv.org)
  3. IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
  4. Grandmaster level in StarCraft II using multi-agent reinforcement learning
  5. Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor (International Conference on Machine Learning)
  6. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
  7. Evaluating Large Language Models Trained on Code (arXiv.org)
  8. Evolution Strategies as a Scalable Alternative to Reinforcement Learning
  9. Backpropagation Through Time: What It Does and How to Do It
  10. D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Their papers