Alternatives and similar repositories for CBDM-pytorch

Users that are interested in CBDM-pytorch are comparing it to the libraries listed below

• yue-zhongqi / diti
  Code release for ICLR 2024 paper: Exploring Diffusion Time-steps for Unsupervised Representation Learning
  ☆32Updated last year
• shiyegao / DDA
  Official repository of "Back to Source: Diffusion-Driven Test-Time Adaptation"
  ☆84Updated 2 years ago
• ML-GSAI / DPT
  Official PyTorch implementation for "Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels"
  ☆96Updated last year
• mihirp1998 / Diffusion-TTA
  Diffusion-TTA improves pre-trained discriminative models such as image classifiers or segmentors using pre-trained generative models.
  ☆79Updated last year
• FutureXiang / ddae
  [ICCV 2023 Oral] Official Implementation of "Denoising Diffusion Autoencoders are Unified Self-supervised Learners"
  ☆183Updated 2 weeks ago
• deeplearning-wisc / dream-ood
  source code for NeurIPS'23 paper "Dream the Impossible: Outlier Imagination with Diffusion Models"
  ☆72Updated 8 months ago
• yu-rp / Distribution-Shift-Iverson
  ☆42Updated 2 years ago
• yongchaoz / diffusion_inversion
  Code for "Training on Thin Air: Improve Image Classification with Generated Data"
  ☆48Updated 2 years ago
• GuoQiushan / EGC
  ☆45Updated 2 years ago
• soumik-kanad / diffssl
  Code for the paper "Do text-free diffusion models learn discriminative visual representations?"
  ☆32Updated 2 years ago
• yossigandelsman / test_time_training_mae
  The official github repo for "Test-Time Training with Masked Autoencoders"
  ☆90Updated 2 years ago
• BierOne / ood_coverage
  [ICLR 2024 Spotlight] Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization
  ☆32Updated last year
• FutureXiang / soda
  Unofficial implementation of "SODA: Bottleneck Diffusion Models for Representation Learning"
  ☆96Updated last year
• mr-eggplant / EATA
  Code for ICML 2022 paper — Efficient Test-Time Model Adaptation without Forgetting
  ☆135Updated 2 years ago
• JegZheng / truncated-diffusion-probabilistic-models
  Pytorch implementation of TDPM
  ☆36Updated 2 years ago
• SHI-Labs / Diffusion-Driven-Test-Time-Adaptation-via-Synthetic-Domain-Alignment
  Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment, arXiv 2024 / CVPR 2025
  ☆37Updated 9 months ago
• vimar-gu / MinimaxDiffusion
  [CVPR2024] Efficient Dataset Distillation via Minimax Diffusion
  ☆103Updated last year
• dongzhuoyao / Diffusion-Representation-Learning-Survey-Taxonomy
  ☆106Updated last year
• gqk / LAE
  [ICCV 2023] A Unified Continual Learning Framework with General Parameter-Efficient Tuning
  ☆90Updated last year
• GeorgeCazenavette / glad
  ☆115Updated 2 years ago
• LINs-lab / RDED
  [CVPR 2024] On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
  ☆80Updated 9 months ago
• daeunni / BECoTTA
  Code for "BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation [ICML2024]".
  ☆45Updated last year
• hunto / DiffKD
  Official implementation for paper "Knowledge Diffusion for Distillation", NeurIPS 2023
  ☆93Updated last year
• LeapLabTHU / ProCo
  [TPAMI 2024] Probabilistic Contrastive Learning for Long-Tailed Visual Recognition
  ☆87Updated last year
• deeplearning-wisc / npos
  source code for ICLR'23 paper "Non-parametric Outlier Synthesis"
  ☆51Updated 2 years ago
• MediaBrain-SJTU / Geometric-Harmonization
  [NeurIPS 2023 Spotlight] Combating Representation Learning Disparity with Geometric Harmonization
  ☆24Updated 7 months ago
• Wang-pengfei / SAGM
  The official codes of our CVPR-2023 paper: Sharpness-Aware Gradient Matching for Domain Generalization
  ☆78Updated 2 years ago
• CVMI-Lab / SyntheticData
  Is synthetic data from generative models ready for image recognition?
  ☆184Updated 2 years ago
• Coxy7 / robust-finetuning
  Official PyTorch implementation of "Masked Images Are Counterfactual Samples for Robust Fine-tuning" (CVPR 2023)
  ☆14Updated 2 years ago
• yzy1996 / Awesome-Generative-Model
  A collection of resources on Generative Model.
  ☆34Updated last year