Bilal Kartal's repositories
pommerman-baseline
Code for the paper "Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition"
60_Days_RL_Challenge
Learn Deep Reinforcement Learning in Depth in 60 days
a3c_continuous
A continuous action space version of A3C LSTM in pytorch plus A3G design
awesome-RLHF
A curated list of reinforcement learning with human feedback resources (continually updated)
cs231n.github.io
Public facing notes page
DeepRL-Tutorials
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
grad-cam-pytorch
PyTorch implementation of Grad-CAM
multiworld
Multitask Environments for RL
mushroom-rl
Python library for Reinforcement Learning experiments.
muzero-general
MuZero
nn
š§ Implementations/tutorials of deep learning papers with side-by-side notes; including transformers (original, xl, switch, feedback), optimizers(adam, radam, adabelief), gans(dcgan, cyclegan), reinforcement learning (ppo, dqn), capsnet, sketch-rnn, etc.
open_spiel
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
pytorch-a3c
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
pytorch-grad-cam
PyTorch implementation of Grad-CAM
random-network-distillation-pytorch
Random Network Distillation pytorch
responsible-ai-widgets
This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.
rl_a3c_pytorch
A3C LSTM Atari with Pytorch plus A3G design
VirtualTaobao
Virtual-Taobao simulators with OpenAI Gym interface
visualize_atari
Code for our paper "Visualizing and Understanding Atari Agents" (https://goo.gl/AMAoSc)
world-models
Reimplementation of World-Models (Ha and Schmidhuber 2018) in pytorch