adapt-python / adapt

Related projects: ⓘ

• KevinMusgrave / pytorch-adapt
  Domain adaptation made easy. Fully featured, modular, and customizable.
  ☆353Updated last year
• mims-harvard / Raincoat
  Domain Adaptation for Time Series Under Feature and Label Shifts
  ☆104Updated last year
• GRichard513 / ADisc-MSDA
  Code for Unsupervised Multi-Source Domain Adaptation for Regression paper
  ☆17Updated 4 years ago
• uchidalab / time_series_augmentation
  An example of time series augmentation methods with Keras
  ☆328Updated 2 years ago
• hfawaz / cd-diagram
  Critical difference diagram with Wilcoxon-Holm post-hoc analysis.
  ☆247Updated 2 years ago
• ChangWeiTan / TS-Extrinsic-Regression
  This repository contains the source code for time series regression.
  ☆94Updated 11 months ago
• cure-lab / deep-active-learning
  An implementation of the state-of-the-art Deep Active Learning algorithms
  ☆97Updated last year
• Wensi-Tang / OS-CNN
  ☆136Updated last year
• yandex-research / rtdl-revisiting-models
  (NeurIPS 2021) Revisiting Deep Learning Models for Tabular Data
  ☆201Updated 4 months ago
• mqwfrog / ULTS
  ULTS: A unified and standardized library of unsupervised representation learning approaches for time series
  ☆39Updated 10 months ago
• emadeldeen24 / AdaTime
  [TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data
  ☆176Updated last year
• thuml / A-Roadmap-for-Transfer-Learning
  ☆152Updated 2 years ago
• BorgwardtLab / Set_Functions_for_Time_Series
  Repository of the ICML 2020 paper "Set Functions for Time Series"
  ☆120Updated 3 years ago
• vanderschaarlab / hyperimpute
  A framework for prototyping and benchmarking imputation methods
  ☆156Updated last year
• ratschlab / GP-VAE
  TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155
  ☆124Updated last year
• zzw-zwzhang / Awesome-of-Time-Series-Augmentation
  A curated list of time series augmentation resources.
  ☆64Updated 2 years ago
• IntelLabs / bayesian-torch
  A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
  ☆509Updated 7 months ago
• White-Link / UnsupervisedScalableRepresentationLearningTimeSeries
  Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments
  ☆393Updated last month
• hturbe / InterpretTime
  Implementation of the InterpretTime framework
  ☆37Updated last year
• BayesWatch / deep-kernel-transfer
  Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
  ☆196Updated 2 years ago
• JakobCode / UncertaintyInNeuralNetworks_Resources
  ☆93Updated 3 years ago
• super-shayan / semi-super-ts-clf
  Code for our paper Self Supervised Learning for Semi Supervised Time Series Classification PAKDD 2020
  ☆16Updated 4 years ago
• JAEarly / MILTimeSeriesClassification
  Inherently Interpretable Time Series Classification via Multiple Instance Learning (MILLET)
  ☆35Updated 6 months ago
• wwweiwei / awesome-self-supervised-learning-for-tabular-data
  A collection of research materials on SSL for non-sequential tabular data (SSL4NSTD)
  ☆149Updated last week
• okrasolar / pytorch-timeseries
  PyTorch implementations of neural networks for timeseries classification
  ☆107Updated 2 years ago
• AlaaLab / deep-learning-uncertainty
  Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…
  ☆597Updated 2 years ago
• edebrouwer / gru_ode_bayes
  Pytorch implementation of GRU-ODE-Bayes
  ☆222Updated 2 years ago
• zhuyitan / IGTD
  Image Generator for Tabular Data (IGTD): Converting Tabular Data to Images for Deep Learning Using Convolutional Neural Networks
  ☆154Updated 3 months ago
• Wensi-Tang / DPSN
  ☆21Updated 11 months ago
• mims-harvard / TFC-pretraining
  Self-supervised contrastive learning for time series via time-frequency consistency
  ☆422Updated 4 months ago