shenzebang's Stars
dmlc/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
DartML/Stein-Variational-Gradient-Descent
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
mariogeiger/hessian
hessian in pytorch
behaviorguidedRL/BGRL
Open source demo for the paper Learning to Score Behaviors for Guided Policy Optimization
YiifeiWang/Optimal-Transport
Group project "Algorithms for large-scale optimal transport". Implement ADMMs and Sinkhorn's Algorithms.
zuoxingdong/mazelab
A customizable framework to create maze and gridworld environments
PythonOT/POT
POT : Python Optimal Transport
ciwang/policydistillation
Reproducing Policy Distillation (DeepMind paper ICLR 2016)
jax-ml/jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
jik0730/MAML-in-pytorch
Neat and flexible implementation of MAML in pytorch: https://arxiv.org/abs/1703.03400
ray-project/ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
ikostrikov/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).
ikostrikov/pytorch-trpo
PyTorch implementation of Trust Region Policy Optimization
Alfredvc/paac
Open source implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning
astooke/rlpyt
Reinforcement Learning in PyTorch
jingweiz/pytorch-rl
Deep Reinforcement Learning with pytorch & visdom
d2l-ai/d2l-zh
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
d2l-ai/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
sweetice/Deep-reinforcement-learning-with-pytorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
google-deepmind/dm_control
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
tristandeleu/pytorch-meta
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
katerakelly/pytorch-maml
PyTorch implementation of MAML: https://arxiv.org/abs/1703.03400
udacity/deep-reinforcement-learning
Repo for the Deep Reinforcement Learning Nanodegree program
higgsfield/RL-Adventure
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
Khrylx/PyTorch-RL
PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.
openai/baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
fKunstner/limitations-empirical-fisher
Limitations of the Empirical Fisher Approximation
AtomicVar/NG-MAML
MAML with Natural Gradient Adaptation
thiagopbueno/gradient-estimators-in-stochastic-computation-graphs
Gradient Estimation in Stochastic Computation Graphs using TensorFlow.