Alternatives and similar repositories for liresnet

Users that are interested in liresnet are comparing it to the libraries listed below

• vasusingla / simple-data-attribution
  A simple and efficient baseline for data attribution
  ☆11Updated last year
• gortizji / linearized-networks
  Source code of "What can linearized neural networks actually say about generalization?
  ☆20Updated 3 years ago
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• mueller-mp / SAM-ON
  ☆34Updated last year
• ethz-spylab / realistic-adv-examples
  Code for the paper "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]
  ☆21Updated last year
• Trustworthy-ML-Lab / Linear-Explanations
  [ICML 24] A novel automated neuron explanation framework that can accurately describe poly-semantic concepts in deep neural networks
  ☆13Updated 4 months ago
• somepago / DCR
  Official Pytorch repo of CVPR'23 and NeurIPS'23 papers on understanding replication in diffusion models.
  ☆111Updated last year
• fra31 / robust-finetuning
  Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"
  ☆19Updated 2 years ago
• ethz-spylab / diffusion_denoised_smoothing
  Certified robustness "for free" using off-the-shelf diffusion models and classifiers
  ☆43Updated 2 years ago
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆61Updated 2 years ago
• nivha / dataset_reconstruction
  ☆59Updated last year
• yangarbiter / rare-spurious-correlation
  Understanding Rare Spurious Correlations in Neural Network
  ☆12Updated 3 years ago
• weizeming / ICML-2024-SAM-AT
  ☆24Updated last year
• YuxinWenRick / diffusion_memorization
  Official repo for Detecting, Explaining, and Mitigating Memorization in Diffusion Models (ICLR 2024)
  ☆76Updated last year
• OPTML-Group / Unlearn-Sparse
  [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…
  ☆77Updated last year
• hamidkazemi22 / CLIPInversion
  What do we learn from inverting CLIP models?
  ☆55Updated last year
• sail-sg / D-TRAK
  Intriguing Properties of Data Attribution on Diffusion Models (ICLR 2024)
  ☆31Updated last year
• locuslab / acr-memorization
  ☆36Updated 8 months ago
• AminJun / ImageNet1KBoundingBoxes
  Pytorch ImageNet1k Loader with Bounding Boxes.
  ☆13Updated 3 years ago
• VITA-Group / Shake-to-Leak
  ☆14Updated 5 months ago
• OPTML-Group / DP4TL
  [NeurIPS2023] "Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning" by Yihua Zhang*, Yimeng Zhang*,…
  ☆13Updated last year
• nvedant07 / Fairness-Through-Robustness
  Official code for FAccT'21 paper "Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning" https://arxiv.org/abs…
  ☆13Updated 4 years ago
• nblt / DLDR
  [TPAMI 2023] Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces
  ☆42Updated 3 years ago
• dedeswim / vits-robustness-torch
  Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]
  ☆52Updated 2 years ago
• NYU-DICE-Lab / circumventing-concept-erasure
  ☆21Updated last year
• stanislavfort / ensemble-everything-everywhere
  The code for the Ensemble everything everywhere: Multi-scale aggregation for adversarial robustness paper
  ☆22Updated 9 months ago
• Trustworthy-ML-Lab / Describe-and-Dissect
  [TMLR 25] An automated method for explaining complex neuron behaviors in deep vision models using large language models
  ☆10Updated 6 months ago
• MadryLab / journey-TRAK
  Code for the paper "The Journey, Not the Destination: How Data Guides Diffusion Models"
  ☆24Updated last year
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 3 years ago
• nv-tlabs / DPDM
  Differentially Private Diffusion Models
  ☆101Updated last year