frankhlchi

frankhlchi's Stars

• princeton-nlp/LESS

  [ICML 2024] LESS: Selecting Influential Data for Targeted Instruction Tuning

  Language:Jupyter Notebook34828

• SJTU-DMTai/awesome-ml-data-quality-papers

  Papers about training data quality management for ML models.

  182

• dair-ai/Prompt-Engineering-Guide

  🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

  Language:MDX49.1k4.8k

• stanford-futuredata/FrugalGPT

  FrugalGPT: better quality and lower cost for LLM applications

  Language:Jupyter Notebook17717

• 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.

  Language:Python273

• frankhlchi/graph-data-valuation

  Language:Jupyter Notebook1

• hans66hsu/GATS

  Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)

  Language:Python201

• frankhlchi/SimEnhancedGCL

  Code for the paper "Enhancing Graph Contrastive Learning with Node Similarity".

  Language:Python1

• 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.

  54350

• JasonZhang156/awesome-mixed-sample-data-augmentation

  A collection of awesome things about mixed sample data augmentation

  13115

• wkiri/simcalib

  Similarity-based classifier calibration

  Language:Python6

• Data-Centric-GraphML/awesome-papers

  A collection of papers and resources about Data-centric Graph Machine Learning (DC-GML).

  434

• iancovert/shapley-regression

  For calculating Shapley values via linear regression.

  Language:Python6414

• opendataval/opendataval

  OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)

  Language:Python837

• flyingdoog/awesome-graph-explainability-papers

  Papers about explainability of GNNs

  64164

• ynchuang/CoRTX-720

  Language:Python101

• deeplearning-wisc/cider

  PyTorch implementation of CIDER (How to exploit hyperspherical embeddings for out-of-distribution detection), ICLR 2023

  Language:Python537

• Amanda-Zheng/Awesome-Data-Centric-GraphML

  A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)

  344

• Amanda-Zheng/GNNEvaluator

  Pytorch implementation for NeurIPS-23:"GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels"

  Language:Python18

• XiaoxinHe/neurips2023_learning_on_graphs

  List of papers on NeurIPS2023

  Language:Python872

• THUMNLab/awesome-graph-ood

  Papers about out-of-distribution generalization on graphs.

  1519

• yuwvandy/TDGNN

  Language:Python192

• yixinliu233/GREET

  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating

  Language:Python484

• alexfanjn/Graph-Neural-Networks-With-Heterophily

  This repository contains the resources on graph neural network (GNN) considering heterophily.

  21620

• 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.

  Language:Python82

• benedekrozemberczki/pytorch_geometric_temporal

  PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

  Language:Python2.6k371

• RexYing/gnn-model-explainer

  gnn explainer

  Language:Python860173

• cuis15/FCFL

  Language:Python201

• shchur/gnn-benchmark

  Framework for evaluating Graph Neural Network models on semi-supervised node classification task

  Language:Python43973

• UW-Madison-Lee-Lab/LanguageInterfacedFineTuning

  Code for Language-Interfaced FineTuning for Non-Language Machine Learning Tasks.

  Language:Jupyter Notebook1207