ZIYU-DEEP / Awesome-Autoencoders-for-Representation-Learning
A curated list on the literature of autoencoders for representation learning.
☆30Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for Awesome-Autoencoders-for-Representation-Learning
- Contains notebooks for the PAR tutorial at CVPR 2021.☆36Updated 3 years ago
- Learning perturbation sets for robust machine learning☆64Updated 3 years ago
- Developing adversarial examples and showing their semantic generalization for the OpenAI CLIP model (https://github.com/openai/CLIP)☆26Updated 3 years ago
- ☆16Updated 2 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆42Updated 3 years ago
- Code for "Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources". (IC…☆37Updated 4 years ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆44Updated 4 years ago
- ☆35Updated last year
- Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"☆22Updated 2 years ago
- This repository holds code and other relevant files for the NeurIPS 2022 tutorial: Foundational Robustness of Foundation Models.☆70Updated last year
- Smooth Adversarial Training☆67Updated 4 years ago
- Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"☆23Updated 5 years ago
- [NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".☆45Updated last year
- A Self-Consistent Robust Error (ICML 2022)☆67Updated last year
- This is the official implementation of ClusTR: Clustering Training for Robustness paper.☆20Updated 3 years ago
- Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)☆17Updated last year
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 2 years ago
- Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2…☆23Updated 4 years ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆89Updated 3 years ago
- ICML 2020, Estimating Generalization under Distribution Shifts via Domain-Invariant Representations☆21Updated 4 years ago
- ICLR Reproducibility Challenge: Generative Adversarial Models For Learning Private And Fair Representations☆11Updated 5 years ago
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).☆51Updated 4 years ago
- Pytorch implementation for "The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction"☆33Updated 2 years ago
- PyTorch implementations of Adversarial defenses and utils.☆34Updated 10 months ago
- ☆29Updated 5 years ago
- Code for the Adversarial Image Detectors and a Saliency Map☆12Updated 7 years ago
- Code for NeurIPS 2019 Paper☆48Updated 4 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated last year
- Implementation for What it Thinks is Important is Important: Robustness Transfers through Input Gradients (CVPR 2020 Oral)☆16Updated last year
- ☆17Updated 2 years ago