This repo provides a federated learning framework that allows to carry out backdoor attacks under varying conditions. This is a keras-tensorflow implementation provided as a Jupyter Notebook which is hopefully self-explanatory.
Paper: Anomaly Localization in Model Gradients Under Backdoor Attacks Against Federated Learning https://arxiv.org/abs/2111.14683
Action Recognition for Self-Driving Cars This repo contains the codes for the 2021 Fall semester project "Action Recognition for Self-Driving Cars" at
This repo holds the codes of our paper: Adaptive Dropblock Enhanced GenerativeAdversarial Networks for Hyperspectral Image Classification, which is ac
PyTorch-High-Res-Stereo-Depth-Estimation Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch. Stereo dep
GainedVAE A Pytorch Implementation of a continuously rate adjustable learned image compression framework, Gained Variational Autoencoder(GainedVAE). N
DIRL: Domain-Invariant Representation Learning Domain-Invariant Representation Learning (DIRL) is a novel algorithm that semantically aligns both the
Description: This is the official implementation of our AAAI-21 accepted paper Label Confusion Learning to Enhance Text Classification Models. The str
Porcupine Made in Vancouver, Canada by Picovoice Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening
Denoised-Smoothing-TF Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow. Denoised Smoothing is
rl_portfolio This Repository uses Reinforcement Learning and Supervised learning to Optimize portfolio allocation. The goal is to make profitable agen
Welcome! I am a computer vision deep learning developer working in Korea. This is my blog, and you can see everything I've studied here. https://www.n
Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b
No RL No Simulation (NRNS) Official implementation of the NRNS paper: No RL, No Simulation: Learning to Navigate without Navigating NRNS is a heriarch
Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari
Generative Adversarial Notebooks Collection of my Generative Adversarial Network implementations Most codes are for python3, most notebooks works on C
1. Requirements CUDA 11.1 TensorRT 7.2.2 Python 3.8.5 Cython PyTorch 1.8.1 torchvision 0.9.1 numpy 1.17.4 (numpy版本过高会出报错 this issue ) python-package s
Documentation: https://mmsegmentation.readthedocs.io/ English | 简体中文 Introduction MMSegmentation is an open source semantic segmentation toolbox based
Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact
A-CNN: Annularly Convolutional Neural Networks on Point Clouds Created by Artem Komarichev, Zichun Zhong, Jing Hua from Department of Computer Science
Simple-implementation-of-Mobile-Former At present, only the model but no trained. There may be some bug in the code, and some details may be different
LightQNet This is a demo code of training and testing [LightQNet] using Tensorflow. Uncertainty Losses: IDQ loss PCNet loss Uncertainty Networks: Mobi
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