nivha / dataset_reconstructionLinks
☆59Updated last year
Alternatives and similar repositories for dataset_reconstruction
Users that are interested in dataset_reconstruction are comparing it to the libraries listed below
Sorting:
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆53Updated 2 years ago
- Differentially Private Diffusion Models☆104Updated last year
- ☆32Updated last year
- ☆88Updated 2 years ago
- Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]☆28Updated 2 years ago
- [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…☆81Updated last year
- The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from t…☆83Updated 3 years ago
- Certified robustness "for free" using off-the-shelf diffusion models and classifiers☆44Updated 2 years ago
- Official Pytorch repo of CVPR'23 and NeurIPS'23 papers on understanding replication in diffusion models.☆113Updated last year
- Code for the paper "Better Diffusion Models Further Improve Adversarial Training" (ICML 2023)☆144Updated 2 years ago
- ☆49Updated last year
- [ICLR24 (Spotlight)] "SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation…☆138Updated 5 months ago
- A simple and efficient baseline for data attribution☆11Updated 2 years ago
- This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.☆22Updated 3 years ago
- Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)☆113Updated 2 years ago
- ☆13Updated 2 years ago
- [TPAMI 2023] Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces☆42Updated 3 years ago
- Official repo for Detecting, Explaining, and Mitigating Memorization in Diffusion Models (ICLR 2024)☆77Updated last year
- What do we learn from inverting CLIP models?☆56Updated last year
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated 2 years ago
- ☆58Updated 5 years ago
- ☆24Updated last year
- [AAAI-2022] Up to 100x Faster Data-free Knowledge Distillation☆74Updated 3 years ago
- Code for CVPR22 paper "Deep Unlearning via Randomized Conditionally Independent Hessians"☆25Updated 3 years ago
- [AAAI, ICLR TP] Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening☆56Updated last year
- Git Re-Basin: Merging Models modulo Permutation Symmetries in PyTorch☆77Updated 2 years ago
- Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion☆11Updated last year
- Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at Neur…☆35Updated last year
- Query-Efficient Data-Free Learning from Black-Box Models☆23Updated 2 years ago
- [ECCV24] "Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, …☆23Updated 5 months ago