A ViT based transformer applied on multi-channel time-series EEG data for motor imagery classification

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"

Self-supervised contrastive learning for time series via time-frequency consistency

A PyTorch implementation of SimCLR based on ICML 2020 paper "A Simple Framework for Contrastive Learning of Visual Representations"

[TPAMI 2023] Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification

PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

A curated list of awesome self-supervised methods

A comprehensive list of awesome contrastive self-supervised learning papers.

[TNNLS-2023] This is the PyTorch implementation of LGGNet.

A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

Anomaly detection related books, papers, videos, and toolboxes

Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

Domain Adaption for sEMG-based Gesture Recognition with Recurrent Neural Networks

EMG feature calculator for putEMG dataset

This repository contains the implementation of Sequential Feature Detachment (SFD) for feature selection and its application to Detach-ROCKET for time series classification.

Code for the paper "POCKET: Pruning Random Convolution Kernels for Time Series Classification from a Feature Selection Perspective'"

Implementations of various feature selection methods

mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.

This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.

open-source feature selection repository in python

Features selector based on the self selected-algorithm, loss function and validation method

Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data

😄博客论文列表：分系列整理

A treasure chest for visual classification and recognition powered by PaddlePaddle

Awesome Knowledge Distillation

Official implementation of paper "Knowledge Distillation from A Stronger Teacher", NeurIPS 2022