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advencoder

The implementation of our ICCV 2023 paper "Downstream-agnostic Adversarial Examples"

arena_3.0

assistance_request

augmented_lagrangian_adversarial_attacks

Code for the ICCV 2021 paper "Augmented Lagrangian Adversarial Attacks"

co-attack

official PyTorch implement of Towards Adversarial Attack on Vision-Language Pre-training Models

coding_theory

coles_project_ml

dash_for_iot

diap

A Data Independent Approach to Generate Adversarial Patches

dragon

это тестовый репозиторий для шалостей

ead-attack

Codes for reproducing the white-box adversarial attacks in “EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples,” AAAI 2018

forecastpfn

fuzzy_time_series

Some code and simulations for my bachelor thesis

greedyfool

GreedyFool (NIPS2020) official code for saprse adversarial attack

modelbiasedattack

multirobustness

Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019

nma_tda_hacklberry

Here's our repository for TDA project for Neuromatch Academy. Exploring persistent homology in mice's brain.

patch-fool

[ICLR 2022] "Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?" by Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin

probability_hse_exams

Probability and statistics exams, Higher School of Economics

sga

Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models. [ICCV 2023]

sgd-uap-torch

Universal Adversarial Perturbations (UAPs) for PyTorch

simmtm

About Code release for "SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling" (NeurIPS 2023 Spotlight), https://arxiv.org/abs/2302.00861

sparse-adversarial-attack

Implementation of ECCV 2020 "Sparse Adversarial Attack via Perturbation Factorization"

sparse-imperceivable-attacks

Sparse and Imperceivable Adversarial Attacks (accepted to ICCV 2019).

sparsefool

A fast sparse attack on deep neural networks.

strattack

StrAttack, ICLR 2019

tabpfn

Official implementation of the TabPFN paper (https://arxiv.org/abs/2207.01848) and the tabpfn package.

tabular-dl-tabr

The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"