Jiaqing Xie's repositories
Theories-of-Graph-Neural-Networks
A List of Papers on Theoretical Foundations of Graph Neural Networks
GuaranteeML
ETH Guarantees for Machine Learning
Probabilistic-Artificial-Intelligence-ETHZ
PAI Projects @ ETHZ
infosec-lab
ETH Zurich Information Security Lab HS2022
GNF-PyTorch
Pytorch-Implementation of Graph Normalizing Flows
Statistical-Learning-Theory-ETHZ
Statistical Learning Theory @ ETH Zurich
awesome-protein-representation-learning
Awesome Protein Representation Learning
ADLG
ETHZ Applications of Deep Learning on Graphs
awesome-graph-reduction
[IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.
awesome-graph-transformer
Papers about graph transformers.
CoRe-GD
Implementation for the paper "CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs"
DeepPurpose
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
DPVO
Deep Patch Visual Odometry
ETH-Principles-of-Microeconomics
ETH Zurich 363-0503-00L Principles of Microeconomics
GCond
[ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"
GFlowNet-GCL
Code for GFlowNet-EM, a novel algorithm for fitting latent variable models with compositional latents and an intractable true posterior.
GNF-pytorch-1
Unofficial Implentation of Graph Normalizing Flows in Pytorch
GraphGPS
Recipe for a General, Powerful, Scalable Graph Transformer
Normalized-Information-Payload
codes for paper: What Dense Graph do You Need for Self-attention?
pytorch-NetVlad
Pytorch implementation of NetVlad including training on Pittsburgh.
reinforced-genetic-algorithm
Structure-based Drug Design; Reinforcement Learning and Genetic Algorithm
SFM-Opt
Implementation and Optimization for Social Force Model for Pedestrian Dynamics
TikZ
Complete collection of my PGF/TikZ figures.
torchdrug
A powerful and flexible machine learning platform for drug discovery
Yale-DLG
Prelease demo on Yale course CPSC 483: Deep Learning on Graph-Structured Data