Sudaorange

Sudaorange's Stars

• xqding/RealNVP

  A PyTorch Implementation of Density Estimation Using Real NVP

  Language:Jupyter Notebook5812

• HongyangGao/Graph-U-Nets

  Pytorch implementation of Graph U-Nets (ICML19)

  Language:Python516101

• ShenggengLin/MDDI-SCL

  Language:Python52

• ShenggengLin/MDF-SA-DDI

  Language:Python226

• microsoft/Drug-Interaction-Research

  7316

• AstraZeneca/chemicalx

  A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

  Language:Python71288

• aangelopoulos/conformal-prediction

  Lightweight, useful implementation of conformal prediction on real data.

  Language:Jupyter Notebook76086

• ml-stat-Sustech/TorchCP

  A Python toolbox for conformal prediction research on deep learning models, using PyTorch.

  Language:Python22731

• gulabpatel/Graph_Neural_Network

  Language:Jupyter Notebook11

• zzyy0929/KDD23-CauSTG

  The appendix and core code of model CauSTG, for accepted paper in KDD 2023.

  Language:Python82

• microsoft/StemGNN

  Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting

  Language:Python507116

• HomuraT/CIDF

  Causal Inference-based Debiasing Framework for Knowledge Graph Completion

  Language:Python8

• ckassaad/causal_discovery_for_time_series

  Causal discovery for time series

  Language:Jupyter Notebook8818

• hanlaoshi/Time-Series-Forecasting-with-Deeplearning

  Paper for Time Series Forecasting with Deeplearning

  Language:Jupyter Notebook6

• pgmpy/pgmpy.github.io

  Docs for pgmpy (Auto-generated using Sphinx; Read-only)

  Language:HTML15

• janishar/mit-deep-learning-book-pdf

  MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

  Language:Java12.8k2.7k

• ioanabica/Time-Series-Deconfounder

  Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. Bica, A. M. Alaa, M. van der Schaar

  Language:Python5114

• LMissher/STWave

  [ICDE'2023] When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks

  Language:Python694

• ShotDownDiane/steve

  Code for STEVE

  Language:Python82

• Wuyxin/DIR-GNN

  Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)

  Language:Python11616

• chenhongkai/Freehand-Machine-Learning

  Language:Python224

• Zhouxiaonnan/machine-learning-notesandcode

  机器学习学习笔记和代码

  Language:Jupyter Notebook9220

• FenTechSolutions/CausalDiscoveryToolbox

  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

  Language:Python1.1k198

• GoudetOlivier/CGNN

  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"

  Language:Python9837

• hzyhhzy/KataGo

  GTP engine and self-play learning in Go

  16933

• zLulus/NotePractice

  My_Note 笔记练习demo

  Language:C#224161

• boyu-ai/Hands-on-RL

  https://hrl.boyuai.com/

  Language:Jupyter Notebook2.4k534

• nsrr/edf-viewer

  MATLAB EDF Viewer

  Language:Matlab164

• ZiyaoWang100/Modified_ElsevierTemplates

  609

• 820fans/NRLPapers

  Must-read papers on network representation learning (NRL) / network embedding (NE)

  Language:TeX1419