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ats

Advanced Terrestrial Simulator (ATS) development

ats-short-course

Files for Amanzi Workshop.

benchmarking_dl_mimiciii

brits

Code of NIPS18 Paper: BRITS: Bidirectional Recurrent Imputation for Time Series

brits-1

convolutional_stream

Convolutional neural network to detect stream line

da-rnn-in-tensorflow-2-and-pytorch

A Tensorflow 2 (Keras) implementation of DA-RNN (A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction, arXiv:1704.02971)

gru-d

GRU-D, a GRU-based model with trainable decays for multivariate time series classification with missing values/irregular samplings

gru-d-1

inspired by 'Recurrent Neural Networks for Multivariate Time Series with Missing Values' pytorch ver

gru-d-2

Gated Recurrent Unit with a Decay mechanism for Multivariate Time Series with Missing Values

mimic-code

MIMIC Code Repository: Code shared by the research community for the MIMIC-III database

npeet

Non-parametric Entropy Estimation Toolbox

pyet

:sunflower: pyet is a Python package to estimate reference and potential evaporation.

pypots

A Python toolbox/library for reality-centric machine learning/deep learning on partially-observed time series with PyTorch, including SOTA models supporting tasks of imputation, classification, clustering, and forecasting on incomplete (irregularly-sampled) multivariate time series with NaN missing values/data. https://arxiv.org/abs/2305.18811

pysheds

:earth_americas: Simple and fast watershed delineation in python.

pytorch-retain

A pytorch implementation of RETAIN, which is an interpretable predictive model for healthcare applications

pytorch-vae

A Collection of Variational Autoencoders (VAE) in PyTorch.

pytorch-vae-tutorial

A simple tutorial of Variational AutoEncoders with Pytorch

rainyday2

RainyDay Rainfall Hazard Analysis System

rsparrow

A system of R scripts and functions for executing and evaluating SPARROW surface water-quality models that generates graphical, map, and tabular output.

saits

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.0851

st-grat

The pytorch implementation of ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed

stgat

STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction

tsl

tsl: a PyTorch library for processing spatiotemporal data.

victoeywilly.github.io

:iphone: App marketing template for Jekyll

vinh_2023

Vinh_2023

vrnn_gru-u

watershed-workflow

Python workflows for data-rich, hyper-resolution simulations of hydrologic models on watersheds.