Fir-lat

Transform2Act

[ICLR 2022 Oral] Official PyTorch Implementation of "Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design".

G-OOD-D

[WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection

eth-cs-notes

Lecture notes and cheatsheets for Master's in Computer Science at ETH Zurich

graph-ood-detection

A curated list of resources for OOD detection with graph data.

Unleashing-Mask

[ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"

DOE

KDD22-OODGAT

This is the implementation of OODGAT from KDD'22: Learning on Graphs with Out-of-Distribution Nodes.

woods_ood

SFAT

[ICLR 2023] "Combating Exacerbated Heterogeneity for Robust Models in Federated Learning"

run

润学全球官方指定GITHUB，整理润学宗旨、纲领、理论和各类润之实例；解决为什么润，润去哪里，怎么润三大问题； 并成为新**人的核心宗教，核心信念。

ttt_cifar_release

TTT Code Release

Awesome-model-inversion-attack

A curated list of resources for model inversion attack (MIA).

Lottery-Ticket-Hypothesis-in-Pytorch

This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.

OOD-detection-using-OECC

Outlier Exposure with Confidence Control for Out-of-Distribution Detection

informative-outlier-mining

We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness of OOD detection to various types of adversarial OOD inputs and establishes state-of-the-art performance.

logitnorm_ood

Official code for ICML 2022: Mitigating Neural Network Overconfidence with Logit Normalization

energy_ood

error-detection

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

OODSurvey

The Official Repository for "Generalized OOD Detection: A Survey"

Awesome-Pruning

A curated list of neural network pruning resources.

poem

PyTorch implementation of POEM (Out-of-distribution detection with posterior sampling), ICML 2022

hidden-networks

gradnorm_ood

On the Importance of Gradients for Detecting Distributional Shifts in the Wild

ttt_imagenet_release

TTT Code Release

AWP

Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"

Geometry-aware-Instance-reweighted-Adversarial-Training

the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral

semisup-adv

Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf

pre-training

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

MART

Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"

auto-attack

Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"