eugenevinitsky

eugenevinitsky's Stars

• google-research/google-research

  Google Research

  Language:Jupyter Notebook34.2k7501.3k7.9k

• gruns/icecream

  🍦 Never use print() to debug again.

  Language:Python9k51135184

• facebookresearch/hydra

  Hydra is a framework for elegantly configuring complex applications

  Language:Python8.8k1291.4k630

• google-deepmind/mujoco

  Multi-Joint dynamics with Contact. A general purpose physics simulator.

  Language:Jupyter Notebook8.1k1061.5k816

• pytorch/rl

  A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

  Language:Python2.3k41629305

• openai/neural-mmo

  Code for the paper "Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents"

  Language:Python1.6k18830262

• google/vizier

  Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

  Language:Python1.5k243195

• ermongroup/ddim

  Denoising Diffusion Implicit Models

  Language:Python1.4k1137206

• patrick-kidger/torchtyping

  Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.

  Language:Python1.4k163633

• marlbenchmark/on-policy

  This is the official implementation of Multi-Agent PPO (MAPPO).

  Language:Python1.3k793296

• PufferAI/PufferLib

  Simplifying reinforcement learning for complex game environments

  Language:Python1.2k51056

• flow-project/flow

  Computational framework for reinforcement learning in traffic control

  Language:Python1.1k51489375

• facebookresearch/rebel

  An algorithm that generalizes the paradigm of self-play reinforcement learning and search to imperfect-information games.

  Language:C++6532633109

• google-deepmind/meltingpot

  A suite of test scenarios for multi-agent reinforcement learning.

  Language:Python60916109122

• facebookresearch/salina

  a Lightweight library for sequential learning agents, including reinforcement learning

  Language:Python426121241

• srush/Autodiff-Puzzles

  Language:Jupyter Notebook3846421

• proroklab/VectorizedMultiAgentSimulator

  VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

  Language:Python33485869

• facebookresearch/nocturne

  A data-driven, fast driving simulator for multi-agent coordination under partial observability.

  Language:Python264134529

• park-project/park

  Language:Python218132255

• eladrich/pyrallis

  Pyrallis is a framework for structured configuration parsing from both cmd and files. Simply define your desired configuration structure as a dataclass and let pyrallis do the rest!

  Language:Python1936137

• huggingface/simulate

  🎢 Creating and sharing simulation environments for embodied and synthetic data research

  Language:Python1903812513

• facebookresearch/dcd

  Implementations of robust Dual Curriculum Design (DCD) algorithms for unsupervised environment design.

  Language:Python1246925

• vitchyr/viskit

  rllab's viskit with some added features

  Language:Python7341335

• cassidylaidlaw/effective-horizon

  Code and data for the paper "Bridging RL Theory and Practice with the Effective Horizon"

  Language:Python42336

• bsarkar321/madrona_rl_envs

  Collection of RL Environments built using Madrona

  Language:Python24015

• hengyuan-hu/jax-vs-pytorch

  Language:Python10100

• cathywu/rl-notes

  Language:Python70

• llama887/ai-car-preference-learning

  A simple self-driving AI car game, which uses NEAT augmented for preference learning research

  Language:Python5

• poprl/poprank

  Language:Python5211

• egoodman92/gpt-4o-scraper

  Language:Python1100