sherjy

sherjy's Stars

• cmhungsteve/Awesome-Transformer-Attention

  An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

  4.5k12630488

• janosh/awesome-normalizing-flows

  Awesome resources on normalizing flows.

  Language:Python1.4k4312122

• DiffEqML/torchdyn

  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

  Language:Jupyter Notebook1.4k27113125

• Zymrael/awesome-neural-ode

  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

  1.3k545146

• snap-stanford/pretrain-gnns

  Strategies for Pre-training Graph Neural Networks

  Language:Python9551763161

• wehos/awesome-graph-transformer

  Papers about graph transformers.

  74620564

• flyingdoog/awesome-graph-explainability-papers

  Papers about explainability of GNNs

  61726663

• patrick-kidger/NeuralCDE

  Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

  Language:Python60820967

• jxzhangjhu/Awesome-LLM-Uncertainty-Reliability-Robustness

  Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models

  60623243

• ENSTA-U2IS-AI/awesome-uncertainty-deeplearning

  This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.

  51528050

• YuliaRubanova/latent_ode

  Code for "Latent ODEs for Irregularly-Sampled Time Series" paper

  Language:Python5072214125

• acbull/GPT-GNN

  Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

  Language:Python477124988

• yandex-research/tab-ddpm

  [ICML 2023] The official implementation of the paper "TabDDPM: Modelling Tabular Data with Diffusion Models"

  Language:Python36863781

• yule-BUAA/DyGLib

  A Library for Dynamic Graph Learning (NeurIPS 2023)

  Language:Python16021727

• doujiang-zheng/Graph-Learning-Reading-List

  Advances on machine learning of graphs, covering the reading list of recent top academic conferences.

  Language:Jupyter Notebook1502016

• PKU-DAIR/SGL

  A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)

  Language:Python1364221

• ranpox/iclr2024-openreview-submissions

  ICLR 2024 OpenReivew Submission Data

  Language:Python131116

• mbilos/neural-flows-experiments

  Experiments for Neural Flows paper

  Language:Python843716

• crisbodnar/ndp

  Official code for the ICLR 2021 paper Neural ODE Processes

  Language:Python71627

• fpour/DGB

  Dynamic Graph Benchmark

  Language:Python652410

• KimMeen/Neural-Temporal-Walks

  [NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs"

  Language:Python50218

• ShaoQiBNU/uplift_model_notes

  uplift模型业界应用总结

  Language:Jupyter Notebook491113

• WhatAShot/ExcelFormer

  The pioneering neural network surpassing extremely-tuned XGboost and Catboost on varied tabular datasets.

  Language:Python42567

• RManLuo/GSNOP

  Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.

  Language:Python30342

• libeineu/ODE-Transformer

  This is a code repository for the ACL 2022 paper "ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation", which redesigns the Transformer architecture from the ODE perspective via using high-order ODE solvers to enhance the residual connections.

  Language:Python28226

• HerreraKrachTeichmann/NJODE

  code for "Neural Jump Ordinary Differential Equations"

  Language:Python27512

• D10Andy/SAD

  Language:Python26146

• Kaike-Zhang/DyTed

  Language:Python12

• yzhang1918/www2023tiger

  Codes for WWW 2023 paper "TIGER: Temporal Interaction Graph Embedding with Restarts"

  Language:Python10211

• TingDang90/CNDP

  Conditional Neural ODE Processes for Individual Disease Progression Forecasting

  Language:Python40