lokali / FedCDHLinks
☆12Updated last year
Alternatives and similar repositories for FedCDH
Users that are interested in FedCDH are comparing it to the libraries listed below
Sorting:
- [TMLR23] FedDAG: Federated DAG Structure Learning☆17Updated 2 years ago
- ☆22Updated 6 years ago
- DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks☆21Updated 3 months ago
- Official Code Repository for the paper - Personalized Subgraph Federated Learning (ICML 2023)☆49Updated 2 years ago
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆99Updated 7 months ago
- Code for Transformed Distribution Matching (TDM) for Missing Value Imputation, ICML 2023☆14Updated 2 years ago
- This repository is the implementation of Federated Graph Classification over Non-IID Graphs.☆44Updated 2 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆28Updated 3 years ago
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆53Updated 2 years ago
- A collection of algorithms of counterfactual explanations.☆50Updated 4 years ago
- A curated list of papers and resources about the distribution shift in machine learning.☆123Updated 2 years ago
- The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era comp…☆96Updated 2 years ago
- 📚 A collection of awesome Causality in ST data papers.☆22Updated last week
- For calculating Shapley values via linear regression.☆70Updated 4 years ago
- A Data-Centric library providing a unified interface for state-of-the-art methods for hardness characterisation of data points.☆25Updated 6 months ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆93Updated last year
- Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)☆82Updated 2 years ago
- 💱 A curated list of data valuation (DV) to design your next data marketplace☆127Updated 7 months ago
- [ICML 2023] Optimizing the Collaboration Structure in Cross-Silo Federated Learning. Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He.☆18Updated 2 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆116Updated 2 years ago
- Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)☆24Updated 3 months ago
- Implementation of the paper: "FedTabDiff: Federated Learning of Diffusion Models for Synthetic Mixed-Type Tabular Data Generation"☆20Updated 10 months ago
- This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".☆22Updated 3 years ago
- [ICLR 2023] "Combating Exacerbated Heterogeneity for Robust Models in Federated Learning"☆31Updated 2 years ago
- FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.☆30Updated last year
- GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)☆49Updated 2 years ago
- ☆12Updated 2 years ago
- Towards Efficient Shapley Value Estimation via Cross-contribution Maximization☆14Updated 3 years ago
- An awesome collection of causality-inspired graph neural networks.☆83Updated 9 months ago
- Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends [NeurIPS 2023]☆10Updated last year