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
OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi
CRGNN Paper ： Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090
Abstract DeeProb-kit is a Python library that implements deep probabilistic models such as various kinds of Sum-Product Networks, Normalizing Flows an
"# SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING" i
Residual Dense Net De-Interlace Filter (RDNDIF) Work in progress deep de-interlacer filter. It is based on the architecture proposed by Bernasconi et
Direct LiDAR Odometry: Fast Localization with Dense Point Clouds DLO is a lightweight and computationally-efficient frontend LiDAR odometry solution w
HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin
Medical-Insurance-Cost-Prediction-using-Machine-learning - Here in this project, I will use regression analysis to predict medical insurance cost for people in different regions, and based on several
DGCNN is the author's re-implementation of Dynamic Graph CNN, which achieves state-of-the-art performance on point-cloud-related high-level tasks including category classification, semantic segmentat
JigsawClustering Jigsaw Clustering for Unsupervised Visual Representation Learning Pengguang Chen, Shu Liu, Jiaya Jia Introduction This project provid
Zero-Cost-NAS Companion code for the ICLR2021 paper: Zero-Cost Proxies for Lightweight NAS tl;dr A single minibatch of data is used to score neural ne
Labels4Free: Unsupervised Segmentation using StyleGAN ICCV 2021 Figure: Some segmentation masks predicted by Labels4Free Framework on real and synthet
Implementations of the algorithms in the paper Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)
Self-Supervised Learning Features self_supervised offers features like modular framework support for multi-gpu training using PyTorch Lightning easy t
arxiv-sanity, but very lite, simply providing the core value proposition of the ability to tag arxiv papers of interest and have the program recommend similar papers.
Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
FullSubNet This Git repository for the official PyTorch implementation of "A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech E
IterMVS official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo' Introduction IterMVS is a novel lear
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