Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with C…

This repository hosts open code that can be used in Innovyze products that support scripting. This includes Ruby for the UI/Exchange, SQL and other useful stuff. We stand on the shoulders of badger…

MIKE+Py: Streamline your MIKE+ workflows

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

Appsilon’s Tiny Shiny Hackathon: Build, Compete, and Win!

Sustainability App for the region of Greater Montreal displaying the work and findings of Mcgill MSSI researchers in the form of interactive dashboards.

A Tutorial for Setting Python Development Environment with VScode and Docker

Code for our WRR paper "Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning"

Flood Peak Prediction....

Practical Guide to Applied Conformal Prediction, published by Packt

Implementation of Convolutional LSTM in PyTorch.

R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''

NIPS2018 paper

Multivariate LSTM Fully Convolutional Networks for Time Series Classification

CNN+BiLSTM+Attention Multivariate Time Series Prediction implemented by Keras

PyTorch Dual-Attention LSTM-Autoencoder For Multivariate Time Series

This repo collects effective multivariate time series clustering codes.

The paper "Learning Representations for Time Series Clustering"

R Package for Time Series Clustering Along with Optimizations for DTW

Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

Implement Reservoir Computing models for time series classification, clustering, forecasting, and much more!

Time series classification and clustering code written in Python.

This project tests the interpretability of the LSTM model developed by Kratzert et al. 2019. Here we tested if the LSTM model which predicts the streamflow of several ungauged basins across the USA…

curvenumber: an R package to calculate Base Flow Index and Curve Number for gauged and ungauged river catchments

Code for our WRR paper "Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning"

[Journal of Hydrology] Generalization of an Encoder-decoder LSTM model for flood prediction in ungauged catchments

Modern Time Series Forecasting with Python 2E, Published by Packt