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allocentric-scene-perception

This repo hosts both the Allocentric Scene Perception (ASP) benchmark and a biologically plausible model for unsupervised segmentation of objects

brax

Massively parallel rigidbody physics simulation on accelerator hardware.

cleanrl

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

cule

CuLE: A CUDA port of the Atari Learning Environment (ALE)

escaping-stochastic-traps-with-aleatoric-mapping-agents

genomic_bottleneck

gruvbox-gantt-charts-with-pgfgantt

gym-minigrid_personal

Minimalistic gridworld package for OpenAI Gym

gymnax-blines

Baselines for gymnax 🤖

how_to_stay_curious_while_avoiding_noisy_tvs

implementations-nfq

Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method

isaacgymenvs

Isaac Gym Reinforcement Learning Environments

jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

minihack

MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research

noreward-rl

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

purejaxrl

Really Fast End-to-End Jax RL Implementations

python-rl

Some Reinforcement Learning in Python

pytorch-cifar-10-autoencoder

This is a reimplementation of the blog post "Building Autoencoders in Keras". Instead of using MNIST, this project uses CIFAR10.

random-network-distillation

Code for the paper "Exploration by Random Network Distillation"

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

sarsa-mountain-car-sutton-and-barto

Implementation of Sutton and Barto SARSA mountain car algorithm, with their tile coding implementation used as features.

self-supervisor.github.io

A minimalist Jekyll theme, ideally designed for your academic site.

sr-learning-resources

Some notebooks and code to help people get started with understanding successor representations using both discrete states and continuous features

streamlit-agent

Reference implementations of several LangChain agents as Streamlit apps

subnetwork-probing

vizdoomgym

OpenAI Gym wrapper for ViZDoom enviroments

wandb_pickle

Wrapper around wandb that makes it easier to do custom python plots.

wandb_scraper