Hansong-Zhang / M3DLinks
AAAI 2024, M3D: Dataset Condensation by Minimizing Maximum Mean Discrepancy
☆25Updated last year
Alternatives and similar repositories for M3D
Users that are interested in M3D are comparing it to the libraries listed below
Sorting:
- ☆14Updated 2 years ago
- [CVPR 2024] On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm☆73Updated 5 months ago
- The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)☆40Updated 2 years ago
- ☆27Updated 2 years ago
- [ICCV 2023] DataDAM: Efficient Dataset Distillation with Attention Matching☆34Updated last year
- ☆29Updated last year
- [NeurIPS2023] "Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning" by Yihua Zhang*, Yimeng Zhang*,…☆13Updated last year
- ☆40Updated 2 years ago
- [CVPR2024 highlight] Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching (G-VBSM)☆28Updated 10 months ago
- Code for our ICML'24 on multimodal dataset distillation☆38Updated 9 months ago
- ☆58Updated 7 months ago
- ☆67Updated 2 years ago
- Official PyTorch implementation of "Multisize Dataset Condensation" (ICLR'24 Oral)☆14Updated last year
- Code for ICML2023 paper, DDGR: Continual Learning with Deep Diffusion-based Generative Replay.☆37Updated last year
- ☆86Updated 2 years ago
- ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching☆102Updated last year
- Efficient Dataset Distillation by Representative Matching☆111Updated last year
- [CVPR2024] Efficient Dataset Distillation via Minimax Diffusion☆95Updated last year
- Official PyTorch implementation for Frequency Domain-based Dataset Distillation [NeurIPS 2023]☆30Updated last year
- Code for ICML 2022 paper — Efficient Test-Time Model Adaptation without Forgetting☆128Updated 2 years ago
- ☆42Updated last year
- ☆26Updated 2 years ago
- Prioritize Alignment in Dataset Distillation☆20Updated 8 months ago
- Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)☆113Updated last year
- Elucidated Dataset Condensation (NeurIPS 2024)☆21Updated 10 months ago
- ☆16Updated last year
- ☆29Updated 2 years ago
- Paper of out of distribution detection and generalization☆56Updated last year
- PyTorch implementation of paper "Dataset Distillation via Factorization" in NeurIPS 2022.☆66Updated 2 years ago
- Official Code for Dataset Distillation using Neural Feature Regression (NeurIPS 2022)☆47Updated 2 years ago