Stars
Tensor decomposition for machine learning (w/ Python implementation)
Intelligent Driving Model Considering Vehicular Dynamics and Heterogeneous Road Environments
Implementation of Q-Transformer, Scalable Offline Reinforcement Learning via Autoregressive Q-Functions, out of Google Deepmind
李宏毅2021/2022/2023春季机器学习课程课件及作业
(NeurIPS '21 Spotlight) IQ-Learn: Inverse Q-Learning for Imitation
Using to predict the highway traffic speed
CAVSim: a traffic simulator for connected and automated vehicles (CAVs)
Source code for paper "FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling"
This is the description of the comparisive car-following dataset for studying driving behaviours when following AVs vs. HVs.
A curated list of Multi-Modal Reinforcement Learning resources (continually updated)
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
Source code for Spatio-Temporal Trajectory Similarity Learning in Road Networks. KDD 2022.
Official implementation of "Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data".
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL)，including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution (DNS) fields without solving NS equations numerically.
A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputatio…
这是一款提高ChatGPT的数据安全能力和效率的插件。并且免费共享大量创新功能，如：自动刷新、保持活跃、数据安全、取消审计、克隆对话、言无不尽、净化页面、展示大屏、拦截跟踪、日新月异、明察秋毫等。让我们的AI体验无比安全、顺畅、丝滑、高效、简洁。
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing
Official repository for the paper "Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations" (NeurIPS 2022)