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
• Huage001 / DatasetFactorization
  PyTorch implementation of paper "Dataset Distillation via Factorization" in NeurIPS 2022.
  ☆67Updated 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
• facebookresearch / augmentation-corruption
  This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".
  ☆46Updated 3 years ago
• MingSun-Tse / Smile-Pruning
  A generic code base for neural network pruning, especially for pruning at initialization.
  ☆31Updated 3 years ago
• zju-vipa / CMI
  [IJCAI-2021] Contrastive Model Inversion for Data-Free Knowledge Distillation
  ☆73Updated 3 years ago
• MingSun-Tse / Regularization-Pruning
  [ICLR'21] Neural Pruning via Growing Regularization (PyTorch)
  ☆82Updated 4 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
• DataDistillation / DataDAM
  [ICCV 2023] DataDAM: Efficient Dataset Distillation with Attention Matching
  ☆33Updated last year
• Daner-Wang / VTC-LFC
  ☆28Updated 3 years ago
• justincui03 / dc_benchmark
  ☆89Updated 2 years ago
• zju-vipa / Fast-Datafree
  [AAAI-2022] Up to 100x Faster Data-free Knowledge Distillation
  ☆76Updated 3 years ago
• VICO-UoE / IT-GAN
  ☆24Updated 2 years ago
• LTH14 / FSKD
  ☆31Updated 5 years ago
• zyxxmu / lottery-jackpots
  Pytorch implementation of our paper accepted by TPAMI 2023 — Lottery Jackpots Exist in Pre-trained Models
  ☆35Updated 2 years ago
• yu-rp / Distribution-Shift-Iverson
  ☆42Updated 2 years ago
• wyzjack / AdaM3
  [ICDM 2023] Momentum is All You Need for Data-Driven Adaptive Optimization
  ☆26Updated last year
• kaiwang960112 / CAFE
  This is a method of dataset condensation, and it has been accepted by CVPR-2022.
  ☆71Updated 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
• meijieru / fast_advprop
  [ICLR 2022]: Fast AdvProp
  ☆35Updated 3 years ago
• illidanlab / ABD
  [ICML2023] Revisiting Data-Free Knowledge Distillation with Poisoned Teachers
  ☆23Updated last year
• DingfanChen / Private-Set
  Official implementation of "Private Set Generation with Discriminative Information" (NeurIPS 2022)
  ☆17Updated 2 years ago
• JngwenYe / PNCloning
  an official PyTorch implementation of the paper "Partial Network Cloning", CVPR 2023
  ☆13Updated 2 years ago
• Piyush-555 / GaussianDistillation
  Data-free knowledge distillation using Gaussian noise (NeurIPS paper)
  ☆15Updated 2 years ago
• snu-mllab / Efficient-Dataset-Condensation
  Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)
  ☆115Updated 2 years ago
• chenbong / PSS-Net
  ☆17Updated 3 years ago
• alexandertheus / Intra-Fusion
  Towards Meta-Pruning via Optimal Transport, ICLR 2024 (Spotlight)
  ☆16Updated last year
• JngwenYe / LIRF
  Code for ECCV 2022 paper “Learning with Recoverable Forgetting”
  ☆21Updated 3 years ago