wumengqi1997

wumengqi1997's Stars

• 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:Python56.2k4581325.8k

• open-mmlab/mmdetection

  OpenMMLab Detection Toolbox and Benchmark

  Language:Python29.6k3728.4k9.5k

• mli/paper-reading

  深度学习经典、新论文逐段精读

  27.1k73002.4k

• Jack-Cherish/python-spider

  :rainbow:Python3网络爬虫实战：淘宝、京东、网易云、B站、12306、抖音、笔趣阁、漫画小说下载、音乐电影下载等

  Language:Python18.3k634816k

• egonSchiele/grokking_algorithms

  Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)

  Language:JavaScript11.7k329513.8k

• eastlakeside/interpy-zh

  📘《Python进阶》（Intermediate Python - Chinese Version）

  Language:CSS6.4k317331.3k

• open-mmlab/mmaction2

  OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

  Language:Python4.3k421.4k1.2k

• d2l-ai/berkeley-stat-157

  Homepage for STAT 157 at UC Berkeley

  Language:Jupyter Notebook3.7k14571.5k

• bighuang624/AI-research-tools

  :hammer:AI 方向好用的科研工具

  2.4k384350

• open-mmlab/mmaction

  An open-source toolbox for action understanding based on PyTorch

  Language:Python1.9k40199352

• zslomo/2019-Autumn-recruitment-experience

  2019届秋招面经集合

  1.8k5510350

• mbadry1/CS231n-2017-Summary

  After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help me to remember and to anyone who would like to know about it. I've skipped some contents in some lectures as it wasn't important to me.

  Language:Python1.5k353460

• Hzzone/Precipitation-Nowcasting

  pytorch implemention of trajGRU.

  Language:Python561619169

• thuml/predrnn-pytorch

  Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.

  Language:Python4481144113

• jhhuang96/ConvLSTM-PyTorch

  ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

  Language:Python39191085

• tsuirak/skills

  个人的技能树仓库，主要包含个人机器学习以及深度学习的笔记

  Language:Jupyter Notebook36050206

• DA-southampton/TRM_tutorial

  Transformer在CV和NLP领域的变体模型的从零解读：Transformer；VIT；Swin Transformer

  3213044

• wbsth/cs50ai

  CS50's Introduction to Artificial Intelligence with Python - projects solutions

  Language:Python1767174

• CzRzChao/SimpleGA

  用python实现简单的遗传算法

  Language:Python1085054

• aserdega/convlstmgru

  Pytorch implementations of ConvLSTM and ConvGRU modules with examples

  Language:Python722320

• zhuozhudd/PyTorch-Course-Note

  Language:Jupyter Notebook641026

• gnosisyuw/CrevNet-Traffic4cast

  Language:Python273126

• vineeths96/Video-Frame-Prediction

  In this repository, we focus on video frame prediction the task of predicting future frames given a set of past frames. We present an Adversarial Spatio-Temporal Convolutional LSTM architecture to predict the future frames of the Moving MNIST Dataset. We evaluate the model on long-term future frame prediction and its performance of the model on out-of-domain inputs by providing sequences on which the model was not trained.

  Language:Python22207

• HPCForge/BubbleML

  A multiphase multiphysics dataset and benchmarks for scientific machine learning

  Language:Python20477

• JaMesLiMers/Frame_Video_Prediction_Pytorch

  frame video prediction algorithm used pytorch on moving minist

  Language:Python20311

• wdf19961118/LSTM

  利用LSTM根据前16帧图像预测第17帧

  Language:Python20114

• abhishekdbihani/compaction_LIGGGHTS

  This repository contains the workflow for creating a bidisperse grain pack and running a uniaxial compaction test on it using LIGGGHTS. Scripts for post-processing (calculating, plotting and visualizing coordination numbers and force chains) are also provided.

  Language:MATLAB15103

• wuhao1938/LIGGGHTS_IN_WINDOWS_10

  Latest version of LIGGGHTS in Windows 10

  Language:Batchfile11202

• wumengqi1997/awesome-cs-books

  经典编程书籍大全，涵盖：计算机系统与网络、系统架构、算法与数据结构、前端开发、后端开发、移动开发、数据库、测试、项目与团队、程序员职业修炼、求职面试等

  1000