XIAOYEJIAYOU

XIAOYEJIAYOU's Stars

• tsinghua-fib-lab/LLM-Agent-Based-Modeling-and-Simulation

  264

• geekan/MetaGPT

  🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

  Language:Python45.3k5.4k

• XIAOYEJIAYOU/Frenet-Strategy

  Language:Python81

• Significant-Gravitas/AutoGPT

  AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

  Language:Python168k44.4k

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python56.4k5.8k

• neetcode-gh/leetcode

  Leetcode solutions

  Language:JavaScript5.7k2.3k

• ZikangZhou/HiVT

  [CVPR 2022] HiVT: Hierarchical Vector Transformer for Multi-Agent Motion Prediction

  Language:Python637121

• ageron/handson-ml2

  A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

  Language:Jupyter Notebook28k12.8k

• ZuodaoTech/everyone-can-use-english

  人人都能用英语

  Language:TypeScript25.2k3.8k

• Avik-Jain/100-Days-Of-ML-Code

  100 Days of ML Coding

  45.5k10.6k

• MLEveryday/100-Days-Of-ML-Code

  100-Days-Of-ML-Code中文版

  Language:Jupyter Notebook21.2k5.5k

• zqzqz/AdvTrajectoryPrediction

  Implementation of CVPR 2022 paper "On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles" https://arxiv.org/abs/2201.05057

  Language:Python9519

• jackfrued/Python-100-Days

  Python - 100天从新手到大师

  Language:Python158k52.5k

• paperswithcode/releasing-research-code

  Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

  2.6k718

• virginiakm1988/ML2022-Spring

  **Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2022 Spring

  Language:Jupyter Notebook2.1k496

• youngyangyang04/leetcode-master

  《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀

  Language:Shell52.1k11.6k

• Henry1iu/TNT-Trajectory-Prediction

  A Unofficial Pytorch Implementation of TNT: Target-driveN Trajectory Prediction

  Language:Python51695

• ckyeungac/DeepIRT

  It is the Deep-IRT model implemented in python3 and tensorflow1.13. Deep-IRT model extends the DKVMN model by cooperating with the IRT model.

  Language:Python5221

• Farama-Foundation/HighwayEnv

  A minimalist environment for decision-making in autonomous driving

  Language:Python2.6k757

• Fafa-DL/Lhy_Machine_Learning

  李宏毅2021/2022/2023春季机器学习课程课件及作业

  Language:Jupyter Notebook6.2k1.6k

• KaihuaTang/Long-Tailed-Recognition.pytorch

  [NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation (LVIS). It is also a PyTorch implementation of the NeurIPS 2020 paper 'Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect'.

  Language:Jupyter Notebook56070

• mli/paper-reading

  深度学习经典、新论文逐段精读

  27.2k2.5k

• microsoft/c9-python-getting-started

  Sample code for Channel 9 Python for Beginners course

  Language:Jupyter Notebook7.8k2.3k

• decrypto-org/blockchain-papers

  A curated list of academic blockchain-related papers

  2.5k559

• facebookresearch/LAMA

  LAnguage Model Analysis

  Language:Python1.4k184

• noambuckman/svo-intersection

  Simulation and code for a socially-compliant intersection manager that coordinates human and autonomous vehicles on the road.

  Language:Jupyter Notebook82

• cjy1992/interp-e2e-driving

  Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning

  Language:Python24339

• XIAOYEJIAYOU/GSAN

  Language:Python101

• rabeehk/hyperformer

  Language:Python15221

• microsoft/ML-For-Beginners

  12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

  Language:HTML69.8k14.5k