Alternatives and similar repositories for ProbMask-official

Users that are interested in ProbMask-official are comparing it to the libraries listed below

• JeanKaddour / WASAM
  Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)
  ☆28Updated 2 years ago
• inspire-group / hydra
  Code and checkpoints of compressed networks for the paper titled "HYDRA: Pruning Adversarially Robust Neural Networks" (NeurIPS 2020) (ht…
  ☆92Updated 2 years ago
• VITA-Group / Alleviate-Robust-Overfitting
  [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…
  ☆47Updated 3 years ago
• da2so / Data-Free_Network_Quantization_With_Adversarial_Knowledge_Distillation
  Data-Free Network Quantization With Adversarial Knowledge Distillation PyTorch
  ☆30Updated 3 years ago
• VITA-Group / triple-wins
  [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“
  ☆24Updated 3 years ago
• alecwangcq / GraSP
  Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH
  ☆105Updated 5 years ago
• JingtongSu / sanity-checking-pruning
  Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot
  ☆42Updated 4 years ago
• VITA-Group / Lifelong-Learning-LTH
  [ICLR 2021] "Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, S…
  ☆25Updated 3 years ago
• nblt / RWP
  ☆11Updated 2 years ago
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 3 years ago
• Saehyung-Lee / DCC
  This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.
  ☆21Updated 3 years ago
• yigitcankaya / Shallow-Deep-Networks
  Source Code for ICML 2019 Paper "Shallow-Deep Networks: Understanding and Mitigating Network Overthinking"
  ☆36Updated last year
• nblt / DLDR
  [TPAMI 2023] Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces
  ☆42Updated 2 years ago
• boone891214 / MEST
  [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…
  ☆18Updated 3 years ago
• stephane-rivaud / ForwardLocalGradient
  This is the official implementation of the ICML 2023 paper - Can Forward Gradient Match Backpropagation ?
  ☆12Updated 2 years ago
• JonasGeiping / fullbatchtraining
  Training vision models with full-batch gradient descent and regularization
  ☆37Updated 2 years ago
• lushleaf / Network-Pruning-Greedy-Forward-Selection
  Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
  ☆21Updated 4 years ago
• ShawnXYang / AT_HE
  ☆35Updated 4 years ago
• amazon-science / normalizer-free-robust-training
  Official implementation of "Removing Batch Normalization Boosts Adversarial Training" (ICML'22)
  ☆19Updated 2 years ago
• deeplearning-wisc / Spurious_OOD
  ☆23Updated 3 years ago
• dydjw9 / Efficient_SAM
  ☆58Updated 2 years ago
• VITA-Group / Nasty-Teacher
  [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…
  ☆81Updated 3 years ago
• BorealisAI / mma_training
  Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"
  ☆34Updated 5 years ago
• LYang-666 / TRGP
  [ICLR 2022] Official Code Repository for "TRGP: TRUST REGION GRADIENT PROJECTION FOR CONTINUAL LEARNING"
  ☆21Updated 2 years ago
• garyzhao / ME-ADA
  "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).
  ☆50Updated 4 years ago
• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 3 years ago
• VITA-Group / Once-for-All-Adversarial-Training
  [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…
  ☆44Updated 3 years ago
• VITA-Group / CV_LTH_Pre-training
  [CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jon…
  ☆69Updated 2 years ago
• mueller-mp / SAM-ON
  ☆34Updated last year
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆89Updated 4 years ago