YaoPhoebeGuo

YaoPhoebeGuo's Stars

• jakesnell/prototypical-networks

  Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

  Language:Python1.1k1331252

• SuperBruceJia/EEG-DL

  A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

  Language:Python9472125223

• facebookresearch/classifier-balancing

  This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020

  Language:Python9442121134

• NetManAIOps/OmniAnomaly

  KDD 2019: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

  Language:Python7351150196

• mims-harvard/TFC-pretraining

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

  Language:Python43553182

• emadeldeen24/TS-TCC

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

  Language:Python368634100

• zhiyuanyou/UniAD

  [NeurIPS 2022 Spotlight] A Unified Model for Multi-class Anomaly Detection

  Language:Python24523628

• alexandrebarachant/Grasp-and-lift-EEG-challenge

  Code and documentation for the winning sollution to the Grasp-and-Lift EEG Detection challenge

  Language:Python21718189

• SuperBruceJia/EEG-Motor-Imagery-Classification-CNNs-TensorFlow

  EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow

  Language:Python2045947

• Eldave93/Seizure-Detection-Tutorials

  A series of tutorials teaching the use of Python for epileptic seizure detection on open-source datasets

  Language:Jupyter Notebook1534449

• tsy935/eeg-gnn-ssl

  Language:Python15211044

• talreiss/Mean-Shifted-Anomaly-Detection

  Mean-Shifted Contrastive Loss for Anomaly Detection (AAAI 2023)

  Language:Python11751423

• AITRICS/EEG_real_time_seizure_detection

  Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic Setting (CHIL 2022)

  Language:Python803530

• zhongyy/Unequal-Training-for-Deep-Face-Recognition-with-Long-Tailed-Noisy-Data

  Code for CVPR2019 paper《Unequal Training for Deep Face Recognition with Long Tailed Noisy Data》

  Language:Python675517

• Sharad24/Epileptic-Seizure-Detection

  Deep Learning, Wavelet Analysis and Fourier Transforms for identification of abnormal EEG in Epilepsy patients

  Language:Jupyter Notebook552210

• DSIP-UPatras/ICASSP2019_TCN

  Improved sEMG-based gesture recognition

  Language:Python545211

• hemanthdv/da-hash

  MatConvNet: CNNs for MATLAB

  Language:Cuda504011

• XiaoxiWei/NeurIPS_BEETL

  This is the NeurIPS BEETL repository (https://beetl.ai)

  Language:Jupyter Notebook35736

• mcd4874/NeurIPS_competition

  code for NeurIPS_competition

  Language:Python26446

• notani/python-glad

  A Python Implementation of GLAD

  Language:Python24419

• SSRSGJYD/Feature-Space-Augmentation-for-Long-Tailed-Data

  Unofficial implementation of ECCV 2020 paper "Feature Space Augmentation for Long-Tailed Data"

  Language:Python22325

• stephanieger/imbalanced-sequence-classification

  Methods for generating synthetic minority data for multivariate temporal data to improve classification accuracy.

  Language:Python14414

• poppinace/ldada

  (TIP'18) An Embarrassingly Simple Approach to Visual Domain Adaptation

  Language:C12106

• zzf495/ICSC

  The implementation of ICSC: Domain Adaptation via Incremental Confidence Samples into Classification

  Language:MATLAB9110

• dfcollazosh/DWCNN_TL

  We introduce a parameter-based approach of cross-subject transfer learning for improving the poor-performing individuals in MI-based BCI systems, pooling data from labeled EEG measurements and psychological questionnaires via kernel embedding. To this end, a Deep\&Wide neural network for MI classification is implemented to pre-train the network from the source domain. Then, the layer parameter layers are transferred to initialize the target network within a fine-tuning procedure to recompute the Multilayer Perceptron-based accuracy. To perform data fusion combining categorical with the real-valued features, we implement the stepwise kernel matching via Gaussian embedding.

  Language:Jupyter Notebook520

• ieeg-portal/ieeg-analytic-tools

  Tools for interacting and analyzing with the ieeg-portal *In development*

  Language:MATLAB31103

• mariehane/prototypical-networks

  A re-implementation of "Prototypical Networks for Few-shot Learning" by Jake Snell, Kevin Swersky, and Richard S. Zemel.

  Language:Python2100

• zhangns07/multiple_source_adaptation

  Language:Jupyter Notebook2201

• cralji/EATWSVM

  Language:MATLAB1

• saeed-hashemi/single-class-classification

  single class classfication on cifar dataset by using Mean Shifted Anomaly Detection Algorithem

  Language:Python1