Official PyTorch repository for GRAM

Official Implementation of DiffPuter: Empowering Diffusion Models for Missing Data Imputation, (ICLR 2025 Spotlight)

Repository of the article "Graph Conditional Flow Matching for Relational Data Generation"

Missing Modality Generation for Recommendaton

Code for Optimal Transport for structured data with application on graphs

[NeurIPS 2024 Spotlight] Code for the paper "Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts"

Hassaku is a(nother) research-oriented Recommender System Framework written mostly in Python and leveraging PyTorch. Hassaku hosts the main procedure for data processing, training, testing, hyperpa…

Personalized Graph-based Retrieval for LLMs Benchmark

[CSUR'24] Multimodal Recommender Systems: A Survey

first commit

Graph Neural Machine: A New Model for Learning with Tabular Data

A framework for prototyping and benchmarking imputation methods

[CIKM'24] Self-Supervision Improves Diffusion Models for Tabular Data Imputation

Official implementation of "Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks"

Repository for CARTE: Context-Aware Representation of Table Entries

SVD-AE: Simple Autoencoders for Collaborative Filtering

[TMLR] GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?

All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.

Official PyTorch implementation of "Fair Sampling in Diffusion Models through Switching Mechanism", AAAI 2024.

Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms

Directional diffusion models

ICLR'24 | Multimodal Patient Representation Learning with Missing Modalities and Labels

Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)

[IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.