hans66hsu

hans66hsu's Stars

• CyC2018/CS-Notes

  :books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

  175k5.3k56650.8k

• 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:Shell50.6k37923611.3k

• yzhao062/anomaly-detection-resources

  Anomaly detection related books, papers, videos, and toolboxes

  Language:Python8.2k283221.7k

• amusi/AI-Job-Notes

  AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）

  5.1k13110636

• naganandy/graph-based-deep-learning-literature

  links to conference publications in graph-based deep learning

  Language:Jupyter Notebook4.7k24814772

• hoya012/awesome-anomaly-detection

  A curated list of awesome anomaly detection resources

  2.7k1315513

• Duan-JM/awesome-papers-fewshot

  Collection for Few-shot Learning

  Language:TeX965398134

• tim-learn/awesome-test-time-adaptation

  Collection of awesome test-time (domain/batch/instance) adaptation methods

  67618148

• gnina/gnina

  A deep learning framework for molecular docking

  Language:C++59130205142

• fjchange/awesome-video-anomaly-detection

  Papers for Video Anomaly Detection, released codes collection, Performance Comparision.

  5813111101

• IntelLabs/bayesian-torch

  A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

  Language:Python509172670

• ila/TUM

  Notes, material and various stuff collected while attended TUM Master's Degree

  Language:HTML43020496

• junkunyuan/Awesome-Domain-Generalization

  Awesome things about domain generalization, including papers, code, etc.

  3555139

• mengliu1998/awesome-deep-gnn

  Papers about developing deep Graph Neural Networks (GNNs)

  30016032

• stephens999/fiveMinuteStats

  A repo of short "vignettes" illustrating statistical concepts

  Language:HTML297152386

• bingzhewei/geom-gcn

  Language:Python2869069

• sagarvegad/Video-Classification-CNN-and-LSTM-

  To classify video into various classes using keras library with tensorflow as back-end.

  Language:Python278106116

• benedekrozemberczki/GraphWaveMachine

  A scalable implementation of "Learning Structural Node Embeddings Via Diffusion Wavelets (KDD 2018)".

  Language:Python1837733

• huawei-noah/BGCN

  A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

  Language:Python1538245

• Kyushik/Predictive-Uncertainty-Estimation-using-Deep-Ensemble

  This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble

  Language:Jupyter Notebook1477230

• hollance/reliability-diagrams

  Reliability diagrams visualize whether a classifier model needs calibration

  Language:Jupyter Notebook1345117

• kaize0409/awesome-few-shot-gnn

  An index of algorithms for few-shot learning/meta-learning on graphs

  1336015

• wuga214/IMPLEMENTATION_Variational-Auto-Encoder

  Simple implementation of Variational Autoencoder

  Language:Python1006326

• davide97l/rl-policies-attacks-defenses

  Adversarial attacks on Deep Reinforcement Learning (RL)

  Language:Jupyter Notebook7622612

• ChunyuanLI/spectral_descriptors

  A collection of spectral descriptors for 3D meshed surfaces

  Language:MATLAB572116

• Luvata/CS330-Stanford-Deep-Multi-Task-and-Meta-Learning

  My notes and assignment solutions for Stanford CS330 (Fall 2019 & 2020) Deep Multi-Task and Meta Learning

  Language:Jupyter Notebook413513

• zxj32/uncertainty-GNN

  Uncertainty Aware Semi-Supervised Learning on Graph Data

  Language:Python39129

• vlivashkin/pygkernels

  Graphs clustering using kernel measures and estimators. Kernel KMeans, Spectral Clustering, Kernel Ward etc.

  Language:Python18307

• PavelCz/rl-adversarial-attack

  Adversarial attacks on deep reinforcement learning

  Language:Python10100

• osimpson/hkpr

  Experiments with heat kernel pagerank.

  Language:Python5201