justincui03 / dc_benchmark
☆81Updated last year
Related projects ⓘ
Alternatives and complementary repositories for dc_benchmark
- Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)☆105Updated last year
- This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.☆20Updated 2 years ago
- Efficient Dataset Distillation by Representative Matching☆107Updated 8 months ago
- [ICLR 2023] Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions☆27Updated last year
- ☆37Updated 2 years ago
- [CVPR 2024] On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm☆52Updated 6 months ago
- [AAAI-2022] Up to 100x Faster Data-free Knowledge Distillation☆67Updated 2 years ago
- The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)☆40Updated last year
- Official Code for Dataset Distillation using Neural Feature Regression (NeurIPS 2022)☆46Updated 2 years ago
- Code for the paper "Efficient Dataset Distillation using Random Feature Approximation"☆36Updated last year
- ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching☆94Updated 5 months ago
- [IJCAI-2021] Contrastive Model Inversion for Data-Free Knowledge Distillation☆68Updated 2 years ago
- [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…☆63Updated 8 months ago
- ☆9Updated last year
- [CVPR23] "Understanding and Improving Visual Prompting: A Label-Mapping Perspective" by Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zha…☆51Updated last year
- Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)☆27Updated last year
- ☆59Updated last year
- ☆23Updated 7 months ago
- ☆21Updated last year
- (Pytorch) Training ResNets on ImageNet-100 data☆52Updated 2 years ago
- [TPAMI 2023] Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces☆40Updated 2 years ago
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆46Updated 3 years ago
- translation of VHL repo in paddle☆25Updated last year
- ☆47Updated 9 months ago
- ☆26Updated last year
- This is a method of dataset condensation, and it has been accepted by CVPR-2022.☆68Updated 11 months ago
- PyTorch implementation of paper "Dataset Distillation via Factorization" in NeurIPS 2022.☆62Updated last year
- [NeurIPS 2022] Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach -- Official Implementation☆44Updated last year
- [ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers☆20Updated 2 years ago
- Code for CVPR22 paper "Deep Unlearning via Randomized Conditionally Independent Hessians"☆25Updated 2 years ago