-
Rutgers University
- New Jersey
- https://sites.google.com/view/huyvnphan
Highlights
- Pro
Stars
The open-sourced Python toolbox for backdoor attacks and defenses.
Official code for the paper RIBAC: Towards Robust and Imperceptible Backdoor Attack against Compact DNN (ECCV 2022)
TrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses) of image classification in deep learning.
Pretrained TorchVision models on CIFAR10 dataset (with weights)
Collection of generative models in Pytorch version.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)
Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"
Code and checkpoints of compressed networks for the paper titled "HYDRA: Pruning Adversarially Robust Neural Networks" (NeurIPS 2020) (https://arxiv.org/abs/2002.10509).
Code for our NeurIPS 2019 *spotlight* "Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers"
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
A Pytorch-Lightning implementation of self-supervised algorithms
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Tensorboard extension for jupyterlab.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423
Companion webpage to the book "Mathematics For Machine Learning"
These are companion notebooks written in Julia and Python for: "Introduction to Applied Linear Algebra" by Boyd and Vandenberghe.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10779
Pytorch implementation of Learning to See in the Dark in CVPR 2018
The winning submission for NIPS 2017: Defense Against Adversarial Attack of team TSAIL