Wenzhao Jiang's Projects
Adaptive Graph Convolutional Recurrent Network
This is a Pytorch implementation of ASTGNN. Now the corresponding paper is available online at https://ieeexplore.ieee.org/document/9346058.
Attention based model for learning to solve different routing problems
Mixing an audio file with a noise file at any Signal-to-Noise Ratio (SNR)
[KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by YongduoSui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua
Script to calculate SNR and SDR using python
The official implementation for "Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment" which is accepted to NeurIPS22.
Here is the codebase for our accepted paper in the Research Track of KDD'23 on 'Causal-Inference-via-Style-Transfer-for-OOD-Generalisation'.
Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"
This is the official release code of AAAI2023 accepted paper: "Causal Conditional Hidden Markov Model for Multimodal Traffic Prediction"
Counterfactual Regression
Reproducing Shalit et al.'s Individual Treatment Effect model. This is a deep neural net that can be applied to various problems in causal inference.
Use ChatGPT to summarize the arXiv papers.
Code for ICML2020 paper - CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Discovering Congestion Propagation Patterns in Spatio-Temporal Traffic Data
Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. Bica, A. M. Alaa, J. Jordon, M. van der Schaar
Official code release for Deep Extreme Mixture Model by Wilson, McDonald, Galib, Tan, and Luo.
Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"
Official code of "Discovering Invariant Rationales for Graph Neural Networks" (2022 ICLR)
NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
[CIKM 2021 Resource Paper] DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction (Graph Part)
[CIKM 2021 Resource Paper] DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction (Grid Part)
Implementation of ECO-DQN as reported in "Exploratory Combinatorial Optimization with Reinforcement Learning".
[Paper] Repository for the paper "On a Guided Nonnegative matrix factorization," a method for guiding the formation of topics using seed words.
This is the repository of HaluEval, a large-scale hallucination evaluation benchmark for Large Language Models.