YaoPhoebeGuo

YaoPhoebeGuo's Stars

• chomeyama/DualCycleGAN

  Official implementation of DualCycleGAN for nonparallel audio super resolution

  Language:Python495

• zkx06111/WSRGlow

  The official implementation of the Interspeech 2021 paper WSRGlow: A Glow-based Waveform Generative Model for Audio Super-Resolution.

  Language:Python12419

• haoheliu/versatile_audio_super_resolution

  Versatile audio super resolution (any -> 48kHz) with AudioSR.

  Language:Python1.1k106

• kuleshov/audio-super-res

  Audio super resolution using neural networks

  Language:Python1.2k205

• slp-rl/aero

  This repo contains the official PyTorch implementation of "Audio Super Resolution in the Spectral Domain" (ICASSP 2023)

  Language:Python19426

• thuml/Time-Series-Library

  A Library for Advanced Deep Time Series Models.

  Language:Python6.2k988

• NeuroTechX/moabb

  Mother of All BCI Benchmarks

  Language:Python670174

• carrtesy/Graph-WaveNet-WaveBound

  Exemplary Implementation of WaveBound (NeurIPS 2022) to Traffic domain, especially GWNet.

  Language:Jupyter Notebook4

• carrtesy/M2N2

  Official repository for the paper "When Model Meets New Normals: Test-time Adaptation for Unsupervised Time-series Anomaly Detection", AAAI 2024.

  Language:Jupyter Notebook174

• tim-learn/awesome-test-time-adaptation

  Collection of awesome test-time (domain/batch/instance) adaptation methods

  66148

• state-spaces/mamba

  Mamba SSM architecture

  Language:Python12.4k1k

• timeseriesAI/tsai

  Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

  Language:Jupyter Notebook5.1k635

• silvia1993/Self-Supervised_Learning_Across_Domains

  6

• xihao-1223/TrafficFlowPredictionResources

  交通流量预测项目在研，以下是本人学习过程中积累整理的资源，会持续更新

  18033

• OpsPAI/MTAD

  MTAD: Tools and Benchmark for Multivariate Time Series Anomaly Detection

  Language:Python8913

• raghavchalapathy/Deep-Learning-for-Anomaly-Detection-A-Survey

  This paper is continuously updated with deep anomaly detection methods and their applications

  Language:TeX10323

• LiDan456/MAD-GANs

  Applied generative adversarial networks (GANs) to do anomaly detection for time series data

  Language:Python511158

• hi-bingo/BeatGAN

  BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series

  Language:Roff6714

• neilzxu/robust_weighted_classification

  Code for "Class-Weighted Classification: Trade-offs and Robust Approaches"

  Language:Python81

• TheDatumOrg/UCRArchiveFixes

  2018 UCR Time-Series Archive: Backward Compatibility, Missing Values, and Varying Lengths

  Language:MATLAB3739

• OpenNMT/OpenNMT-py

  Open Source Neural Machine Translation and (Large) Language Models in PyTorch

  Language:Python6.7k2.2k

• finloop/usad-torchlightning

  Implementation of USAD (UnSupervised Anomaly Detection on multivariate time series) in PyTorch Lightning

  Language:Python181

• White-Link/UnsupervisedScalableRepresentationLearningTimeSeries

  Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

  Language:Jupyter Notebook39393

• braindecode/braindecode

  Deep learning software to decode EEG, ECG or MEG signals

  Language:Python775174

• kashif/pytorch-transformer-ts

  Repository of Transformer based PyTorch Time Series Models

  Language:Jupyter Notebook28541

• garrettj403/SciencePlots

  Matplotlib styles for scientific plotting

  Language:Python6.9k699

• haoshileii/micos

  Language:Python82

• ilkyyldz95/EEG_MVTS

  Language:Python91

• EdisonLeeeee/MaskGAE

  [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders

  Language:Python736

• THUDM/GraphMAE

  GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22

  Language:Python45474