frankhlchi's Stars
dair-ai/Prompt-Engineering-Guide
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
benedekrozemberczki/pytorch_geometric_temporal
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
RexYing/gnn-model-explainer
gnn explainer
flyingdoog/awesome-graph-explainability-papers
Papers about explainability of GNNs
ENSTA-U2IS-AI/awesome-uncertainty-deeplearning
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
shchur/gnn-benchmark
Framework for evaluating Graph Neural Network models on semi-supervised node classification task
princeton-nlp/LESS
[ICML 2024] LESS: Selecting Influential Data for Targeted Instruction Tuning
alexfanjn/Graph-Neural-Networks-With-Heterophily
This repository contains the resources on graph neural network (GNN) considering heterophily.
stanford-futuredata/FrugalGPT
FrugalGPT: better quality and lower cost for LLM applications
THUMNLab/awesome-graph-ood
Papers about out-of-distribution generalization on graphs.
JasonZhang156/awesome-mixed-sample-data-augmentation
A collection of awesome things about mixed sample data augmentation
UW-Madison-Lee-Lab/LanguageInterfacedFineTuning
Code for Language-Interfaced FineTuning for Non-Language Machine Learning Tasks.
opendataval/opendataval
OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
XiaoxinHe/neurips2023_learning_on_graphs
List of papers on NeurIPS2023
chr26195/PMLP
This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", which is accepted to ICLR 2023.
iancovert/shapley-regression
For calculating Shapley values via linear regression.
deeplearning-wisc/cider
PyTorch implementation of CIDER (How to exploit hyperspherical embeddings for out-of-distribution detection), ICLR 2023
yixinliu233/GREET
[AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
Data-Centric-GraphML/awesome-papers
A collection of papers and resources about Data-centric Graph Machine Learning (DC-GML).
Amanda-Zheng/Awesome-Data-Centric-GraphML
A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)
liujl11git/GNN-LP
[ICLR 2023 spotlight] "On Representing Linear Programs by Graph Neural Networks" by Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin.
SJTU-DMTai/awesome-ml-data-quality-papers
Papers about training data quality management for ML models.
hans66hsu/GATS
Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)
cuis15/FCFL
yuwvandy/TDGNN
Amanda-Zheng/GNNEvaluator
Pytorch implementation for NeurIPS-23:"GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels"
ynchuang/CoRTX-720
wkiri/simcalib
Similarity-based classifier calibration
frankhlchi/graph-data-valuation
frankhlchi/SimEnhancedGCL
Code for the paper "Enhancing Graph Contrastive Learning with Node Similarity".