hch1017's Stars
yuetan031/FedProto
[AAAI'22] FedProto: Federated Prototype Learning across Heterogeneous Clients
litian96/ditto
Ditto: Fair and Robust Federated Learning Through Personalization (ICML '21)
HumanCompatibleAI/imitation
Clean PyTorch implementations of imitation and reward learning algorithms
DLR-RM/stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
CVxTz/time_series_forecasting
fuxiAIlab/RL4RS
A Real-World Benchmark for Reinforcement Learning based Recommender System
google-research/recsim
A Configurable Recommender Systems Simulation Platform
QikaiXu/Recommender-System-Pytorch
基于 Pytorch 实现推荐系统相关的算法
nikhilbarhate99/PPO-PyTorch
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
tianrang-intelligence/TSCC2019
Traffic Signal Control Competition
multi-commander/Multi-Commander
Multi & Single Agent Reinforcement Learning for Traffic Signal Control Problem
traffic-signal-control/RL_signals
All you need to know about Reinforcement Learning for Traffic Signal Control. https://traffic-signal-control.github.io/
wingsweihua/gym_cityflow
Adds CityFlow to Gym
Housiadas/forecasting-energy-consumption-LSTM
Development of a machine learning application for IoT platform to predict electric energy consumption in smart building environment in real time.
Dokyyy/IPDALight
IPDALight for traffic signal control
quan-possible/energy-demand-prediction
moe221/SARIMA_Power_Demand_Prediction
Repo for building electricity demand classification & prediciton project
KuanWeiBeCool/Predict-Electricity-Demand-in-Ontario
This repository contains files and code for the project - "Forecasting Ontario’s Electrical Demand Using Machine Learning" - authored by Kuan Wei, Lucas Crea, Manuel Sage, and Jiarui Xie. We collected the hourly electricity demand in Ontario from the years 2017 to 2020 (https://www.ieso.ca/en/Power-Data/Data-Directory). Other features used for the predictions include time (converted into sine-cosine encoding), temperature (a weighted average temperature across six weather stations in the major population centers across the province: Hamilton, Kitchener, London, Ottawa, Toronto and Windsor, from https://climate.weather.gc.ca), and holiday information. Four machine learning models (RF, FCNN, LSTM, GRU) are used and their model performances are compared.
TalwalkarLab/leaf
Leaf: A Benchmark for Federated Settings
BY571/Soft-Actor-Critic-and-Extensions
PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.
Nicolinho/ACC
Source code for Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning
SamsungLabs/tqc_pytorch
Implementation of Truncated Quantile Critics method for continuous reinforcement learning. https://bayesgroup.github.io/tqc/
gorkemalgan/deep_learning_with_noisy_labels_literature
This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.
AI4Finance-Foundation/ElegantRL
Massively Parallel Deep Reinforcement Learning. 🔥
dyhan0920/PyramidNet-PyTorch
A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, https://arxiv.org/abs/1610.02915)
higgsfield/RL-Adventure
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
shaoxiongji/federated-learning
A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561
CharlieDinh/pFedMe
Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)
dxyang/DQN_pytorch
Vanilla DQN, Double DQN, and Dueling DQN implemented in PyTorch
vy007vikas/PyTorch-ActorCriticRL
PyTorch implementation of DDPG algorithm for continuous action reinforcement learning problem.