xiaowangfeng

xiaowangfeng's Stars

• hjkgrp/MOFSimplify

  The MOF website for property prediction and community engagement.

  Language:C++276

• meiirbek-islamov/thermal-transport-MOFs

  6

• YKQ98/Matformer

  Official code for Periodic Graph Transformers for Crystal Material Property Prediction (NeurIPS 2022)

  Language:Python736

• superlouis/GATGNN

  Pytorch Repository for our work: Graph convolutional neural networks with global attention for improved materials property prediction

  Language:Python6717

• usnistgov/alignn

  Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ&hl=en

  Language:Python19979

• materialsvirtuallab/matgl

  Graph deep learning library for materials

  Language:Python24358

• materialsvirtuallab/megnet

  Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

  Language:Jupyter Notebook493155

• WangYueFt/dgcnn

  Language:Python1.6k419

• dair-ai/ml-visuals

  🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

  12.9k1.4k

• shap/shap

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

  Language:Jupyter Notebook22.2k3.2k

• leo6862/pointattentionvlad

  PointAttentionVLAD : A two-stage self-attenion network for point cloud based place recognition

  Language:Python41

• Andrew-S-Rosen/QMOF

  The QMOF Database: A database of quantum-mechanical properties for metal-organic frameworks.

  Language:Python11525

• zhuty16/MQSA-TED

  This is our Tensorflow implementation for "Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation." (MQSA-TED) WSDM 2024.

  Language:Python61

• MenghaoGuo/PCT

  Jittor implementation of PCT:Point Cloud Transformer

  Language:Python64880

• JierunChen/FasterNet

  [CVPR 2023] Code for PConv and FasterNet

  Language:Python66054

• YOLOonMe/EMA-attention-module

  Implementation Code for the ICCASSP 2023 paper " Efficient Multi-Scale Attention Module with Cross-Spatial Learning" and is available at: https://arxiv.org/abs/2305.13563v2

  1569

• xmindflow/Awesome_Mamba

  Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis

  16311

• YuanbinLiu/GANN

  Multiscale Graph Attention Neural Networks for Mapping Materials and Molecules

  4

• brain-research/mpnn

  Open source implementation of "Neural Message Passing for Quantum Chemistry"

  Language:Python23155

• lmy1997/tuxiaoshi

  Language:Python17115

• Xiaoxun-Gong/DeepH-E3

  Language:Python6016

• deepmodeling/DeepH-pack

  Deep neural networks for density functional theory Hamiltonian.

  Language:Python116

• txie-93/cgcnn

  Crystal graph convolutional neural networks for predicting material properties.

  Language:Python616300

• txie-93/cdvae

  An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]

  Language:Python21788

• deepmaterials/dlmatreview

  https://www.nature.com/articles/s41524-022-00734-6

  Language:TeX10923

• munrojm/pymatgen

  Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.

  Language:HTML1

• materialsproject/api

  New API client for the Materials Project

  Language:Python10636

• cal-itp/data-infra

  Cal-ITP data infrastructure

  Language:Python4412

• googleapis/google-cloud-go

  Google Cloud Client Libraries for Go.

  Language:Go3.7k1.2k

• google-deepmind/materials_discovery

  Language:Python845132