Alternatives and similar repositories for differentially-private-q-learning

Users that are interested in differentially-private-q-learning are comparing it to the libraries listed below

• gnobitab / MultiObjectiveSampling
  ☆18Updated 4 years ago
• pokaxpoka / netrand
  Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning / ICLR 2020
  ☆56Updated 5 years ago
• pengyang7881187 / FedRL
  Hao Jin, Yang Peng, Wenhao Yang, Shusen Wang and Zhihua Zhang. Federated Reinforcement Learning with Environment Heterogeneity. AISTATS, …
  ☆63Updated 3 years ago
• glenn89 / FederatedRL
  ☆39Updated 3 years ago
• VITA-Group / L2O-Training-Techniques
  [NeurIPS 2020 Spotlight Oral] "Training Stronger Baselines for Learning to Optimize", Tianlong Chen*, Weiyi Zhang*, Jingyang Zhou, Shiyu …
  ☆29Updated 4 years ago
• JunjieYang97 / stocBiO
  Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"
  ☆50Updated 4 years ago
• epfml / ChocoSGD
  Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356
  ☆75Updated 5 years ago
• skumar9876 / FCRL
  Implementation of "Federated Control with Hierarchical Multi-Agent Deep Reinforcement Learning" (https://arxiv.org/pdf/1712.08266.pdf)
  ☆38Updated 7 years ago
• FRL2019 / FRL
  ☆42Updated 6 years ago
• alshedivat / fedpa
  Federated posterior averaging implemented in JAX
  ☆53Updated 2 years ago
• gd-zhang / Follow-the-Ridge
  Minimax Optimization, Stackelberg Games, Generative Adversarial Networks
  ☆19Updated 5 years ago
• PKU-RL / FEN
  FEN Code
  ☆40Updated 6 years ago
• google-deepmind / interval-bound-propagation
  This repository contains a simple implementation of Interval Bound Propagation (IBP) using TensorFlow: https://arxiv.org/abs/1810.12715
  ☆161Updated 6 years ago
• zafarali / policy-gradient-methods
  Modular PyTorch implementation of policy gradient methods
  ☆25Updated 7 years ago
• tuomaso / radial_rl
  Code used in our paper "Robust Deep Reinforment Learning through Adversarial Loss"
  ☆33Updated 2 years ago
• obastani / viper
  ☆28Updated 5 years ago
• daniellevy / fast-dro
  PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets
  ☆64Updated 3 years ago
• wangjksjtu / rl-perturbed-reward
  Reinforcement Learning with Perturbed Reward, AAAI 2020
  ☆30Updated last year
• sauxpa / neural_exploration
  Study NeuralUCB and regret analysis for contextual bandit with neural decision
  ☆99Updated 4 years ago
• VITA-Group / L2O-Minimax
  [ICLR 2021] "Learning a Minimax Optimizer: A Pilot Study" by Jiayi Shen*, Xiaohan Chen*, Howard Heaton*, Tianlong Chen, Jialin Liu, Wotao…
  ☆15Updated 4 years ago
• MilesCranmer / gnn_resource_allocation
  Code for our paper on doing resource allocation with graph neural networks
  ☆32Updated 4 years ago
• chenhongge / StateAdvDRL
  [NeurIPS 2020, Spotlight] Code for "Robust Deep Reinforcement Learning against Adversarial Perturbations on Observations"
  ☆139Updated 4 years ago
• chenhongge / SA_DQN
  [NeurIPS 2020, Spotlight] State-Adversarial DQN (SA-DQN) for robust deep reinforcement learning
  ☆35Updated 4 years ago
• ermongroup / lag-fairness
  ☆22Updated 6 years ago
• nuwuxian / RL_attack
  ☆27Updated 2 years ago
• nuwuxian / RL_adv_valuediff
  ☆16Updated 2 years ago
• prolearner / hypertorch
  ☆126Updated last year
• fiezt / ICML-2020-Implicit-Stackelberg-Learning
  ☆12Updated 5 years ago
• arobey1 / LipSDP
  LipSDP - Lipschitz Estimation for Neural Networks
  ☆71Updated 3 years ago
• hongzimao / input_driven_rl_example
  Variance Reduction for Reinforcement Learning in Input-Driven Environments (ICLR '19)
  ☆31Updated 6 years ago