Alternatives and similar repositories for GP-VAE:

Users that are interested in GP-VAE are comparing it to the libraries listed below

• edebrouwer / gru_ode_bayes
  Pytorch implementation of GRU-ODE-Bayes
  ☆230Updated 2 years ago
• BorgwardtLab / Set_Functions_for_Time_Series
  Repository of the ICML 2020 paper "Set Functions for Time Series"
  ☆123Updated 4 years ago
• probabilistic-learning / HI-VAE
  ☆90Updated 2 years ago
• mlds-lab / interp-net
  Code for "Interpolation-Prediction Networks for Irregularly Sampled Time Series", ICLR 2019.
  ☆94Updated 7 months ago
• boschresearch / Continuous-Recurrent-Units
  ☆63Updated last year
• felixykliu / NAOMI
  ☆51Updated 5 years ago
• reml-lab / mTAN
  Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.
  ☆128Updated 3 years ago
• NIPS-BRITS / BRITS
  ☆81Updated 2 years ago
• ratschlab / dpsom
  Code associated with ACM-CHIL 21 paper 'T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States'
  ☆68Updated 4 years ago
• abudesai / timeVAE
  TimeVAE implementation in keras/tensorflow
  ☆141Updated 9 months ago
• mbohlkeschneider / gluon-ts
  GluonTS - Probabilistic Time Series Modeling in Python
  ☆51Updated 3 years ago
• pamattei / miwae
  Implementation of the MIWAE method for deep generative modelling of incomplete data sets.
  ☆37Updated last year
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆46Updated last year
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆113Updated last year
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆92Updated last year
• PeterChe1990 / GRU-D
  GRU-D, a GRU-based model with trainable decays for multivariate time series classification with missing values/irregular samplings
  ☆125Updated 2 years ago
• Han-JD / GRU-D
  inspired by 'Recurrent Neural Networks for Multivariate Time Series with Missing Values' pytorch ver
  ☆113Updated 6 years ago
• zhiyongc / GRU-D
  Gated Recurrent Unit with a Decay mechanism for Multivariate Time Series with Missing Values
  ☆115Updated 5 years ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆74Updated 4 months ago
• ayaabdelsalam91 / TS-Interpretability-Benchmark
  ☆90Updated 3 years ago
• KurochkinAlexey / IMV_LSTM
  Pytorch implementation of "Exploring Interpretable LSTM Neural Networks over Multi-Variable Data" https://arxiv.org/pdf/1905.12034.pdf
  ☆107Updated 5 years ago
• JonathanCrabbe / Dynamask
  This repository contains the implementation of Dynamask, a method to identify the features that are salient for a model to issue its pred…
  ☆74Updated 2 years ago
• sanatonek / time_series_explainability
  ☆59Updated 4 years ago
• ratschlab / SOM-VAE
  TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199
  ☆195Updated 2 years ago
• caow13 / BRITS
  Code of NIPS18 Paper: BRITS: Bidirectional Recurrent Imputation for Time Series
  ☆212Updated 6 years ago
• IvanBongiorni / GAN-RNN_Timeseries-imputation
  Recurrent GAN for imputation of time series data. Implemented in TensorFlow 2 on Wikipedia Web Traffic Forecast dataset from Kaggle.
  ☆173Updated 2 years ago
• jwyyy / AdaFNN
  [ICML 2021] Deep Learning for Functional Data Analysis with Adaptive Basis Layers
  ☆25Updated 2 years ago
• dhanajitb / GAIN-Pytorch
  Pytorch implementation of GAIN for missing data imputation
  ☆72Updated last year
• Harry24k / MIDA-pytorch
  PyTorch implementation of "MIDA: Multiple Imputation using Denoising Autoencoders"
  ☆28Updated 6 years ago
• causalens / cdml-neurips2020
  This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…
  ☆59Updated 7 months ago