huytransformer/Awesome-Out-Of-Distribution-Detection

Out-of-distribution detection, robustness, and generalization resources. The repository contains a curated list of papers, tutorials, books, videos, articles and open-source libraries etc

Size: 501 KB - Last synced at: about 22 hours ago - Pushed at: 8 days ago - Stars: 911 - Forks: 74

MinghuiChen43/awesome-trustworthy-deep-learning

A curated list of trustworthy deep learning papers. Daily updating...

Size: 7.6 MB - Last synced at: about 22 hours ago - Pushed at: 13 days ago - Stars: 366 - Forks: 35

thuml/Transfer-Learning-Library

Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

Language: Python - Size: 13.7 MB - Last synced at: 6 days ago - Pushed at: about 1 year ago - Stars: 3,672 - Forks: 568

divelab/GOOD

GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]

Language: Python - Size: 16.9 MB - Last synced at: 1 day ago - Pushed at: 3 months ago - Stars: 196 - Forks: 19

nikitadurasov/torch-ttt

A modular and easy-to-use framework for Test-Time Training (TTT) and Test-Time Adaptation (TTA) in Pytorch, making your networks more generalizable with minimal effort ✨

Language: Python - Size: 2.83 MB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 18 - Forks: 0

THUMNLab/awesome-graph-ood

Papers about out-of-distribution generalization on graphs.

Size: 4.88 KB - Last synced at: 15 days ago - Pushed at: almost 2 years ago - Stars: 167 - Forks: 9

deep-real/TRO

The Pytorch implementation for "Topology-aware Robust Optimization for Out-of-Distribution Generalization" (ICLR 2023)

Language: Python - Size: 1.16 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 27 - Forks: 3

gifale95/NSD-synthetic

Code to reproduce the results from the NSD-synthetic data release paper.

Language: Python - Size: 5.98 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 3 - Forks: 0

divelab/LECI

The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS 2023)

Language: Python - Size: 166 KB - Last synced at: 1 day ago - Pushed at: 6 months ago - Stars: 19 - Forks: 3

Allliance/TRODO

Official PyTorch implementation of "Scanning Trojaned Models Using Out-of-Distribution Samples" (NeurIPS 2024)

Language: Jupyter Notebook - Size: 1.29 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

juangamella/causal-chamber-paper

Code to reproduce the case studies of the 2024 paper "The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology" by Juan L. Gamella, Jonas Peters and Peter Bühlmann.

Language: Jupyter Notebook - Size: 26.7 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 12 - Forks: 0

hosseinshn/Velodrome

Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics

Language: Python - Size: 2.09 MB - Last synced at: 28 days ago - Pushed at: over 3 years ago - Stars: 17 - Forks: 2

deepmancer/rss-training-iclr2024

This is the official repository for the ICLR 2024 paper Out-Of-Domain Unlabeled Data Improves Generalization.

Language: TeX - Size: 31 MB - Last synced at: 7 months ago - Pushed at: 8 months ago - Stars: 4 - Forks: 0

bratjay01/Road-Seg

Enhancing road segmentation model for Asphalt edge detection

Language: Jupyter Notebook - Size: 16.9 MB - Last synced at: 7 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

LFhase/GALA

[NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

Language: Python - Size: 1.4 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 15 - Forks: 1

qitianwu/IDCF

Code for ICML21 spotlight paper "Towards open-world recommendation: An inductive model-based collaborative filtering approach"

Language: Python - Size: 79.1 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 25 - Forks: 6

LFhase/FeAT

[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization

Language: Python - Size: 434 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 23 - Forks: 1

mala-lab/ADShift

Official PyTorch implementation of the ICCV'23 paper “Anomaly Detection under Distribution Shift”

Language: Python - Size: 59.6 KB - Last synced at: 12 months ago - Pushed at: over 1 year ago - Stars: 21 - Forks: 3

LFhase/CIGA

[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

Language: Python - Size: 618 KB - Last synced at: 12 months ago - Pushed at: over 1 year ago - Stars: 94 - Forks: 9

etetteh/OoD_Gen-Chest_Xray

Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models

Language: Python - Size: 355 KB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 1

xuanlinli17/large_vlm_distillation_ood

Distilling Large Vision-Language Model with Out-of-Distribution Generalizability (ICCV 2023)

Language: Python - Size: 3.69 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 41 - Forks: 4

LFhase/PAIR

[ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization

Language: Jupyter Notebook - Size: 1.22 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 47 - Forks: 3

wondergo2017/sild

Implementation codes for NeurIPS23 paper "Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts"

Language: Python - Size: 2.29 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

qitianwu/GraphOOD-GNNSafe

The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"

Language: Python - Size: 2.37 MB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 64 - Forks: 4

tangli-udel/DRE

The Pytorch implementation for "Are Data-driven Explanations Robust against Out-of-distribution Data?" (CVPR 2023)

Language: Python - Size: 175 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 7 - Forks: 2

yangnianzu0515/MoleOOD

Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022).

Language: Python - Size: 105 MB - Last synced at: about 1 year ago - Pushed at: about 2 years ago - Stars: 50 - Forks: 6

AHHHZ975/FedDG-Extension

This is an extension and re-implementation and of the work "FedDG"

Language: Python - Size: 5.13 GB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

ZigeW/SODA

[NeurIPS 2023] “SODA: Robust Training of Test-Time Data Adaptors”

Language: Python - Size: 21.5 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 1

kdhht2334/ELIM_FER

[NeurIPS 2022] The official repository of Expression Learning with Identity Matching for Facial Expression Recognition

Language: Python - Size: 54.1 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 28 - Forks: 3

ForeverPs/PoER

Potential energy ranking for domain generalization (DG)

Language: Python - Size: 5.66 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 18 - Forks: 1

qitianwu/GraphOOD-EERM

The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"

Language: Python - Size: 3.48 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 40 - Forks: 3

VirtuosoResearch/Distribution-Shifts-in-CMNIST

Language: Python - Size: 502 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

qitianwu/FATE

Codes and datasets for NeurIPS21 paper “Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach”

Language: Python - Size: 46.9 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 17 - Forks: 9

wooks527/G-CPA

GradCAM-based Copy and Paste Augmentation

Language: Python - Size: 196 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

gnyanesh-bangaru/loss-analysis-cka

This work is a analysis of representations acquired for standard, OOD and Biased data on numerous objective functions.

Language: Jupyter Notebook - Size: 203 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0