peterljq / Tutorial-of-Data-Distillation-and-Condensation
A comprehensive overview of Data Distillation and Condensation (DDC). DDC is a data-centric task where a representative (i.e., small but training-effective) batch of data is generated from the large dataset.
☆13Updated last year
Related projects ⓘ
Alternatives and complementary repositories for Tutorial-of-Data-Distillation-and-Condensation
- [ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun…☆37Updated 2 years ago
- A pytorch implementation of the ICCV2021 workshop paper SimDis: Simple Distillation Baselines for Improving Small Self-supervised Models☆14Updated 3 years ago
- ☆16Updated 2 years ago
- Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation☆43Updated last year
- Code for ICLR 2022 Paper, "Controlling Directions Orthogonal to a Classifier"☆34Updated last year
- [ICML 2021] "Efficient Lottery Ticket Finding: Less Data is More" by Zhenyu Zhang*, Xuxi Chen*, Tianlong Chen*, Zhangyang Wang☆25Updated 2 years ago
- Paper List for In-context Learning 🌷☆20Updated last year
- ☆17Updated 2 years ago
- Code of "Visualizing and Understanding Object Detecor"☆20Updated 3 years ago
- [ICLR 2021] "Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, S…☆23Updated 2 years ago
- ☆17Updated 3 years ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆35Updated 3 years ago
- Code for Double Blind CollaborativeLearning (DBCL)☆14Updated 3 years ago
- ☆40Updated last year
- Official implementation of "Private Set Generation with Discriminative Information" (NeurIPS 2022)☆17Updated last year
- Automated neural architecture search algorithms implemented in PyTorch and Autogluon toolkit.☆12Updated 4 years ago
- kyleliang919 / Uncovering-the-Connections-BetweenAdversarial-Transferability-and-Knowledge-Transferabilitycode for ICML 2021 paper in which we explore the relationship between adversarial transferability and knowledge transferability.☆17Updated last year
- This is a PyTorch implementation of the paperViP A Differentially Private Foundation Model for Computer Vision☆37Updated last year
- ☆26Updated 2 years ago
- Implementation for What it Thinks is Important is Important: Robustness Transfers through Input Gradients (CVPR 2020 Oral)☆16Updated last year
- ☆13Updated 2 years ago
- DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization☆28Updated last year
- Experiments from "The Generalization-Stability Tradeoff in Neural Network Pruning": https://arxiv.org/abs/1906.03728.☆14Updated 4 years ago
- Self-Distillation with weighted ground-truth targets; ResNet and Kernel Ridge Regression☆17Updated 3 years ago
- [ICLR 2021: Spotlight] Source code for the paper "A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Infer…☆15Updated 2 years ago
- ICME2022 Special Session “Beyond Accuracy: Responsible, Responsive, and Robust Multimedia Retrieval ”☆11Updated 5 months ago
- ☆22Updated last year
- Code for "Implicit Normalizing Flows" (ICLR 2021 spotlight)☆34Updated 3 years ago
- Interpolation between Residual and Non-Residual Networks, ICML 2020. https://arxiv.org/abs/2006.05749☆26Updated 4 years ago