annafabris / Poisoning-unlabeled-Dataset-for-Semi-Supervised-Learning
A Semi-supervised learning model (Ladder Network) to classify MNIST digits. A few attacks were executed on it with the target of misclassifying 4s with 9s.
☆10Updated 2 years ago
Alternatives and similar repositories for Poisoning-unlabeled-Dataset-for-Semi-Supervised-Learning:
Users that are interested in Poisoning-unlabeled-Dataset-for-Semi-Supervised-Learning are comparing it to the libraries listed below
- This is a Pytorch Implementation of the DASP algorithm from the paper "Explaining Deep Neural Networks with a Polynomial Time Algorithm f…☆10Updated 4 years ago
- [ACMMM 2020] Code release for "Simultaneous Semantic Alignment Network for Heterogenous Domain Adaptation" https://arxiv.org/abs/2008.01…☆30Updated 3 years ago
- ☆23Updated 2 years ago
- Python (PyTorch) realization of Deep Feature Selection (Model, Algorithm)☆17Updated 4 years ago
- This is the implementation for the ICASSP-2022 paper (Confidence-Aware Multi-Teacher Knowledge Distillation).☆56Updated 3 years ago
- Unsupervised Multi-source Domain Adaptation Without Access to Source Data (CVPR '21 Oral)☆58Updated 2 years ago
- Post-selection inference based on truncated Gaussians for the HSIC-Lasso feature selection procedure☆10Updated 3 years ago
- The implementation and addtional material of AAAI2020 paper "Stable Learning via Sample Reweighting"☆16Updated 5 years ago
- This is an official PyTorch implementation of the ICLR 2023 paper 《Free Lunch for Domain Adversarial Training: Environment Label Smoothin…☆59Updated 2 years ago
- ☆9Updated 4 years ago
- Look-Ahead Data Acquisition via Augmentation for Deep Active Learning (NeurIPS 2021)☆14Updated 11 months ago
- This is an official PyTorch implementation of the ICML 2023 paper AdaNPC and SIGKDD paper DRM.☆86Updated last year
- popular concept drift evaluation datasets☆11Updated 5 years ago
- [ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers☆21Updated 3 years ago
- Implementation of "Dual Mixup Regularized Learning for Adversarial Domain Adaptation" in Pytorch☆13Updated 4 years ago
- This is the implementation for the ICME-2023 paper (Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning).☆22Updated 2 years ago
- Code for the paper: "Supervised contrastive learning over prototype-label embeddings for network intrusion detection"☆14Updated 3 years ago
- A collection of resources for graph-based semi-supervised learning (GSSL).☆18Updated 3 years ago
- A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.☆59Updated 3 years ago
- MLTI for ICLR 2022☆30Updated 2 years ago
- This is a comprehensive list of Heterogeneous Transfer Learning methods with their resource (paper, code and data).☆27Updated 9 months ago
- Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning☆44Updated 2 years ago
- Label-Noise Learning with Intrinsically Long-Tailed Data(ICCV2023)☆19Updated last year
- This is the source code for Maximum Mean Discrepancy Test is Aware of Adversarial Attacks (ICML2021).☆19Updated 2 years ago
- Final Project for AM 207, Fall 2021. Review & experimentation with paper "Adversarial Examples Are Not Bugs, They Are Features"☆10Updated 3 years ago
- Official code release for the NeurIPS 2021 article Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time…☆10Updated 3 years ago
- There are my Pytorch codes for charactering adversarial subspace using local intrinsic dimensionality.☆13Updated 3 years ago
- Enhanced Transport Distance for Unsupervised Domain Adaptation☆12Updated 5 years ago
- Official repo for AAAI 2023 paper "Stable Learning via Sparse Variable Independence".☆13Updated 10 months ago
- Code for CAiDA☆24Updated 2 years ago