Alternatives and similar repositories for LPF-SGD:

Users that are interested in LPF-SGD are comparing it to the libraries listed below

• nblt / RWP
  ☆11Updated 2 years ago
• AngusDujw / SAF
  ☆35Updated 2 years ago
• mueller-mp / SAM-ON
  ☆34Updated last year
• nblt / DLDR
  [TPAMI 2023] Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces
  ☆40Updated 2 years ago
• nblt / TWA
  [ICLR 2023] Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions
  ☆26Updated 2 months ago
• yueb17 / DLTH
  ☆30Updated 3 years ago
• ehuynh1106 / TinyImageNet-Transformers
  Transformers trained on Tiny ImageNet
  ☆54Updated 2 years ago
• JeanKaddour / WASAM
  Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)
  ☆28Updated 2 years ago
• tml-epfl / sam-low-rank-features
  Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]
  ☆28Updated last year
• MingSun-Tse / Smile-Pruning
  A generic code base for neural network pruning, especially for pruning at initialization.
  ☆30Updated 2 years ago
• verbiiyo / rigl-torch
  Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.
  ☆56Updated 3 years ago
• x-zho14 / ProbMask-official
  Implementation of Effective Sparsification of Neural Networks with Global Sparsity Constraint
  ☆31Updated 3 years ago
• Shiweiliuiiiiiii / In-Time-Over-Parameterization
  [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…
  ☆45Updated last year
• MingSun-Tse / Awesome-Pruning-at-Initialization
  [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.
  ☆59Updated last year
• justincui03 / dc_benchmark
  ☆86Updated 2 years ago
• VITA-Group / GraNet
  [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
  ☆31Updated 2 years ago
• nsfzyzz / loss_landscape_taxonomy
  [NeurIPS 2021] code for "Taxonomizing local versus global structure in neural network loss landscapes" https://arxiv.org/abs/2107.11228
  ☆19Updated 3 years ago
• jayroxis / CKA-similarity
  An Numpy and PyTorch Implementation of CKA-similarity with CUDA support
  ☆89Updated 3 years ago
• hoonyyhoon / Synflow_SNIP_GraSP
  Comparison of method "Pruning at initialization prior to training" (Synflow/SNIP/GraSP) in PyTorch
  ☆16Updated 11 months ago
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 2 years ago
• varun19299 / rigl-reproducibility
  Reproducing RigL (ICML 2020) as a part of ML Reproducibility Challenge 2020
  ☆28Updated 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
• dydjw9 / Efficient_SAM
  ☆57Updated 2 years ago
• MarlonBecker / MSAM
  ☆18Updated last year
• jaeho-lee / layer-adaptive-sparsity
  In progress.
  ☆63Updated last year
• danielchyeh / ImageNet-100-Pytorch
  (Pytorch) Training ResNets on ImageNet-100 data
  ☆56Updated 3 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
• zhichao-lu / robust-residual-network
  Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective
  ☆20Updated 10 months 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
• Mi-Peng / Sparse-Sharpness-Aware-Minimization
  [NeurIPS 2022] Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach -- Official Implementation
  ☆44Updated last year