tomvii

tomvii's Stars

• openai/weak-to-strong

  Language:Python2.5k3218305

• frgfm/torch-cam

  Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

  Language:Python2k1160207

• benedekrozemberczki/awesome-gradient-boosting-papers

  A curated list of gradient boosting research papers with implementations.

  Language:Python1k493155

• mlfoundations/datacomp

  DataComp: In search of the next generation of multimodal datasets

  Language:Python650176455

• jhayes14/adversarial-patch

  PyTorch implementation of adversarial patch

  Language:Python1992429

• BobXWu/TopMost

  A Topic Modeling System Toolkit

  Language:Jupyter Notebook1862514

• HanxunH/Unlearnable-Examples

  [ICLR2021] Unlearnable Examples: Making Personal Data Unexploitable

  Language:Python14941917

• mwxely/AIGS

  AI-Generated Images as Data Source: The Dawn of Synthetic Era

  Language:TeX1456011

• wl-zhao/DiffSwap

  [CVPR 2023] DiffSwap is a diffusion-based face-swapping framework.

  Language:Python10452612

• mansheej/data_diet

  Language:Python1014224

• SCLBD/BlackboxBench

  Language:Python913716

• apple/ml-dr

  A light-weight implementation of ICCV2023 paper "Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement."

  Language:Python771103

• lhfowl/adversarial_poisons

  Language:Python481411

• cvlab-columbia/ZSRobust4FoundationModel

  Language:Python38372

• tokaka22/GMAA

  Language:Python38166

• TreeLLi/APT

  One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models

  Language:Python36222

• TLMichael/Delusive-Adversary

  [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training

  Language:Python31202

• WentaoChen0813/SemanticPrompt

  Language:Python313103

• kaiwenzha/contrastive-poisoning

  [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning

  Language:Python28201

• mo666666/When-Adversarial-Training-Meets-Vision-Transformers

  Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at NeurIPS 2022.

  Language:Python28274

• haizhongzheng/Coverage-centric-coreset-selection

  Language:Python26211

• umd-huang-lab/Dynamics-Aware-Robust-Training

  ICLR 2023 paper "Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness" by Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein and Furong Huang

  Language:Python21203

• ziquanliu/CVPR2023-TWINS

  Official code for "TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization", CVPR 2023

  Language:Python13125

• he-y/you-only-condense-once

  You Only Condense Once: Two Rules for Pruning Condensed Datasets (NeurIPS 2023)

  Language:Python11100

• val-iisc/OAAT

  Official Code for Scaling Adversarial Training to Large Perturbation Bounds (ECCV-2022)

  Language:Python91313

• matanle51/DIAL

  Domain Invariant Adversarial Learning

  Language:Python8101

• yiweifengyan/NTU-SCSE-Academic-Workflows

  Guidelines for Scholarship Renew / Annual Progress Report, Qualifying Examination and Graduate Training Programme / Graduate Assistantship Programme

  7200

• silvercherry/Improving-Robust-Fairness-via-Balance-Adversarial-Training

  Language:Python5212

• WenbinLee/DefensiveFSL

  The Pytorch code of "Defensive Few-Shot Learning", TPAMI 2023.

  Language:Python5200

• AnonymousCodeRepo/ANP

  Language:Python31