xholc

xholc's Stars

• JasonYao81000/CV2017Fall

  Computer Vision I 2017 Fall at NTU

  Language:Python156

• careercup/CtCI-6th-Edition

  Cracking the Coding Interview 6th Ed. Solutions

  Language:Java11.3k4.4k

• NVIDIA/NeMo

  A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

  Language:Python11.5k2.4k

• triton-inference-server/server

  The Triton Inference Server provides an optimized cloud and edge inferencing solution.

  Language:Python8.1k1.5k

• huggingface/pytorch-image-models

  The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

  Language:Python31.5k4.7k

• google-research/big_vision

  Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.

  Language:Jupyter Notebook2.2k147

• google-research/vision_transformer

  Language:Jupyter Notebook10.1k1.3k

• miladfa7/Social-Network-Analysis-in-Python

  Social Network Facebook Analysis (Python, Networkx)

  Language:Jupyter Notebook367

• dreadlesss/rdkit_summary

  rdkit总结与实践

  Language:Jupyter Notebook20286

• pytorch/captum

  Model interpretability and understanding for PyTorch

  Language:Python4.8k489

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook22.5k3.3k

• adalke/mmpdb

  A package to identify matched molecular pairs and use them to predict property changes.

  Language:Python242

• mahendra-awale/medchem_moves

  Language:Python4415

• rdkit/mmpdb

  A package to identify matched molecular pairs and use them to predict property changes.

  Language:Python20455

• microsoft/molecule-generation

  Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

  Language:Python26042

• scikit-learn-contrib/hdbscan

  A high performance implementation of HDBSCAN clustering.

  Language:Jupyter Notebook2.8k496

• muhanzhang/SEAL

  SEAL (learning from Subgraphs, Embeddings, and Attributes for Link prediction). "M. Zhang, Y. Chen, Link Prediction Based on Graph Neural Networks, NeurIPS 2018 spotlight".

  Language:C588138

• chemprop/chemprop

  Message Passing Neural Networks for Molecule Property Prediction

  Language:Python1.7k570

• gbouritsas/GSN

  Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxiv.org/abs/2006.09252

  Language:Python9420

• ysig/GraKeL

  A scikit-learn compatible library for graph kernels

  Language:Python59396

• snap-stanford/pretrain-gnns

  Strategies for Pre-training Graph Neural Networks

  Language:Python958161

• PurdueMINDS/RelationalPooling

  Language:Python358

• JiaruiFeng/KP-GNN

  Source code for how powerful are K-hop message passing graph neural networks (Neurips 2022)

  Language:Python614

• O-GNN/O-GNN

  Language:Python132

• graphcore/ogb-lsc-pcqm4mv2

  The OGB-LSC is the Large Scale Competition by Open Graph Benchmark to help accelerate research into machine learning on graph structured data

  Language:Jupyter Notebook6614

• rampasek/GraphGPS

  Recipe for a General, Powerful, Scalable Graph Transformer

  Language:Python646115

• benedekrozemberczki/karateclub

  Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

  Language:Python2.1k244

• hadarser/ProvablyPowerfulGraphNetworks_torch

  Language:Python395

• weihua916/benchmarking-gnns

  Repository for benchmarking graph neural networks

  1

• benedekrozemberczki/awesome-graph-classification

  A collection of important graph embedding, classification and representation learning papers with implementations.

  Language:Python4.7k742