Alternatives and similar repositories for DaSS

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

• 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…
  ☆40Updated 2 years ago
• pprp / CVPR2022-NAS-competition-Track1-3th-solution
  Implementation of PGONAS for CVPR22W and RD-NAS for ICASSP23
  ☆22Updated 2 years ago
• skhu101 / GM-NAS
  Code for our ICLR'2022 paper "Generalizing Few-Shot NAS with Gradient Matching"
  ☆22Updated 2 years ago
• VITA-Group / ViT-Anti-Oversmoothing
  [ICLR 2022] "Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice" by Peihao Wang, Wen…
  ☆79Updated last year
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆32Updated 2 years ago
• shoaibahmed / blockwise_ssl
  Repository containing code for blockwise SSL training
  ☆29Updated 7 months ago
• shawnricecake / search-llm
  [NeurIPS 2024] Search for Efficient LLMs
  ☆14Updated 4 months ago
• ziplab / SN-Netv2
  [ECCV 2024] This is the official implementation of "Stitched ViTs are Flexible Vision Backbones".
  ☆27Updated last year
• TencentARC / pi-Tuning
  Official code for "pi-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation", ICML 2023.
  ☆33Updated last year
• NVlabs / SMCP
  ☆21Updated 2 years ago
• zju-vipa / training_free_model_merging
  This repository is the implementation of the paper Training Free Pretrained Model Merging (CVPR2024).
  ☆28Updated last year
• OpenGVLab / LLMPrune-BESA
  BESA is a differentiable weight pruning technique for large language models.
  ☆16Updated last year
• sndnyang / Diffusion_ViT
  PyTorch Implementation of "Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model"
  ☆49Updated 2 years ago
• facebookresearch / ViP-MAE
  This is a PyTorch implementation of the paperViP A Differentially Private Foundation Model for Computer Vision
  ☆36Updated last year
• HubHop / vit-attention-benchmark
  Benchmarking Attention Mechanism in Vision Transformers.
  ☆18Updated 2 years ago
• ziplab / EcoFormer
  [NeurIPS 2022 Spotlight] This is the official PyTorch implementation of "EcoFormer: Energy-Saving Attention with Linear Complexity"
  ☆72Updated 2 years ago
• yukimasano / single-img-extrapolating
  Repo for the paper "Extrapolating from a Single Image to a Thousand Classes using Distillation"
  ☆36Updated 10 months ago
• imagination-research / LCSC
  [ICLR 2025] Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
  ☆14Updated 3 months ago
• MingSun-Tse / Smile-Pruning
  A generic code base for neural network pruning, especially for pruning at initialization.
  ☆30Updated 2 years ago
• OSVAI / NORM
  The official project website of "NORM: Knowledge Distillation via N-to-One Representation Matching" (The paper of NORM is published in IC…
  ☆20Updated last year
• MingSun-Tse / Good-DA-in-KD
  [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective
  ☆37Updated 2 years ago
• changlin31 / AutoProg
  (CVPR 2022) Automated Progressive Learning for Efficient Training of Vision Transformers
  ☆25Updated 3 months ago
• AvivNavon / DWSNets
  Official implementation for Equivariant Architectures for Learning in Deep Weight Spaces [ICML 2023]
  ☆89Updated last year
• mtkresearch / shortest-path-diffusion
  Official code for the paper "Image generation with shortest path diffusion" accepted at ICML 2023.
  ☆23Updated last year
• VITA-Group / Diverse-ViT
  [CVPR 2022] "The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy" by Tianlong C…
  ☆25Updated 3 years ago
• VITA-Group / WeakNAS
  [NeurIPS 2021] “Stronger NAS with Weaker Predictors“, Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang W…
  ☆27Updated 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
• BeSpontaneous / Scala-pytorch
  Scala(NeurIPS 2024)
  ☆10Updated 6 months ago
• megvii-research / TPS-CVPR2023
  ☆45Updated last year
• alexandertheus / Intra-Fusion
  Towards Meta-Pruning via Optimal Transport, ICLR 2024 (Spotlight)
  ☆16Updated 6 months ago