Alternatives and similar repositories for PEMN

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

• MingSun-Tse / Good-DA-in-KD
  [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective
  ☆37Updated 3 years ago
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆34Updated 2 years ago
• MingSun-Tse / Regularization-Pruning
  [ICLR'21] Neural Pruning via Growing Regularization (PyTorch)
  ☆82Updated 4 years ago
• MingSun-Tse / Smile-Pruning
  A generic code base for neural network pruning, especially for pruning at initialization.
  ☆31Updated 3 years ago
• AngusDujw / FTD-distillation
  The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)
  ☆40Updated 2 years ago
• Huage001 / DatasetFactorization
  PyTorch implementation of paper "Dataset Distillation via Factorization" in NeurIPS 2022.
  ☆67Updated 3 years ago
• zju-vipa / CMI
  [IJCAI-2021] Contrastive Model Inversion for Data-Free Knowledge Distillation
  ☆73Updated 3 years ago
• Daner-Wang / VTC-LFC
  ☆28Updated 3 years ago
• facebookresearch / augmentation-corruption
  This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".
  ☆46Updated 3 years ago
• yongchaoz / FRePo
  Official Code for Dataset Distillation using Neural Feature Regression (NeurIPS 2022)
  ☆48Updated 3 years ago
• jiawangbai / HAT
  Implementation of HAT https://arxiv.org/pdf/2204.00993
  ☆51Updated last year
• zyxxmu / lottery-jackpots
  Pytorch implementation of our paper accepted by TPAMI 2023 — Lottery Jackpots Exist in Pre-trained Models
  ☆35Updated 2 years ago
• MingSun-Tse / Why-the-State-of-Pruning-so-Confusing
  [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…
  ☆41Updated 4 months ago
• justincui03 / dc_benchmark
  ☆89Updated 3 years ago
• VICO-UoE / IT-GAN
  ☆24Updated 2 years ago
• wyzjack / AdaM3
  [ICDM 2023] Momentum is All You Need for Data-Driven Adaptive Optimization
  ☆26Updated last year
• iCGY96 / APR
  [ICCV 2021] Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain
  ☆80Updated 3 years ago
• illidanlab / ABD
  [ICML2023] Revisiting Data-Free Knowledge Distillation with Poisoned Teachers
  ☆23Updated last year
• chenbong / PSS-Net
  ☆17Updated 3 years ago
• yu-rp / Distribution-Shift-Iverson
  ☆42Updated 2 years ago
• zju-vipa / Fast-Datafree
  [AAAI-2022] Up to 100x Faster Data-free Knowledge Distillation
  ☆76Updated 3 years ago
• zju-vipa / MosaicKD
  [NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data
  ☆45Updated 3 years ago
• LTH14 / FSKD
  ☆31Updated 5 years ago
• yueb17 / DLTH
  ☆32Updated 3 years ago
• VITA-Group / BackRazor_Neurips22
  [Neurips 2022] “ Back Razor: Memory-Efficient Transfer Learning by Self-Sparsified Backpropogation”, Ziyu Jiang*, Xuxi Chen*, Xueqin Huan…
  ☆20Updated 2 years ago
• ModelTC / L2_Compression
  ☆13Updated last year
• xiusu / ViTAS
  Code for ViTAS_Vision Transformer Architecture Search
  ☆51Updated 4 years ago
• SHI-Labs / DiSparse-Multitask-Model-Compression
  [CVPR 2022] DiSparse: Disentangled Sparsification for Multitask Model Compression
  ☆14Updated 3 years ago
• JngwenYe / PNCloning
  an official PyTorch implementation of the paper "Partial Network Cloning", CVPR 2023
  ☆13Updated 2 years ago
• AlexeyGB / batch-norm-helps-optimization
  Reproduction of "How Does Batch Normalization Help Optimization?" paper
  ☆21Updated 6 years ago