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3dhumanpose

17-joint 3D Human Pose estimation from Single RGB Images

acme

A library of reinforcement learning components and agents

auto-attack

Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

b16examples

blockbased_synapseaware

Block-Based Synapse Aware Skeleton Generation

connected-components-3d

26, 18, and 6 Connected Multi-Label Connected Components on 3D Images

diffusion-relative-rewards

Code for the 2023 NeurIPS paper "Extracting Reward Functions from Diffusion Models"

duckietown-intnav

Intersection Navigation for Duckietown

expandcomponent

Grow Neurons (6-connected components), given their soma voxels.

gym-minigrid

Minimalistic gridworld package for OpenAI Gym

gym-multigrid

Lightweight multi-agent gridworld Gym environment

hellofresh

Code for the 2024 ACL paper "HelloFresh: LLM Evaluations on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits".

illu-attacks-jax

Code for the ICLR 2024 Paper "Illusory Attacks: Information-theoretic detectability matters in adversarial attacks"

imitation

Clean PyTorch implementations of imitation and reward learning algorithms

inverse-reinforcement-learning

Implementations of selected inverse reinforcement learning algorithms.

irl-maxent

Maximum Entropy and Maximum Causal Entropy Inverse Reinforcement Learning Implementation in Python

lbf

A multi-agent environment for RL

maddpg

Pytorch implementation of the MARL algorithm, MADDPG, which correspondings to the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments".

metairl

Meta-Inverse Reinforcement Learning with Probabilistic Context Variables

minerl

MineRL Competition for Sample Efficient Reinforcement Learning - Python Package

minerl2020_submission

minerl_singularity

mpc_climate_control

Model Predictive Control Algorithm for temperature regulation of a delivery truck

nips_figures

pettingzoo

Gym for multi-agent reinforcement learning

pfrl

PFRL: a PyTorch-based deep reinforcement learning library

policy-value-methods

Deep Reinforcement Learning algorithms for Policy Value methods written from scratch.

pyro4

Pyro 4.x - Python remote objects

rl-starter-files

RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code

seals

Benchmark environments for reward modelling and imitation learning algorithms.