wgmueller1

graphstorm

Enterprise graph machine learning framework for billion-scale graphs for ML scientists and data scientists.

evaporate

This repo contains data and code for the paper "Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes"

table-transformer

Table Transformer (TATR) is a deep learning model for extracting tables from unstructured documents (PDFs and images). This is also the official repository for the PubTables-1M dataset and GriTS evaluation metric.

feature_engine

Feature engineering package with sklearn like functionality

website_tutorials

This repository contains tutorials published on [My personal website](https://jlealtru.github.io/)

FastRP

Code for the CIKM 2019 Paper "Fast and Accurate Network Embeddings via Very Sparse Random Projection"

CIRCA

Causal Inference-based Root Cause Analysis

pytorch-ts

PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

incubator-liminal

Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validation, deployment and inference in production. Liminal provides a Domain Specific Language to build ML workflows on top of Apache Airflow.

GCond

[ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"

ES-RNN

bandits

Bayesian Bandits

example-models

Example models for Stan

awesome-explainable-graph-reasoning

A collection of research papers and software related to explainability in graph machine learning.

triangular-tpp

Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)

s4

Structured state space sequence models

gnn-residual-correlation

gnn

TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

Time-series-classification-and-clustering-with-Reservoir-Computing

Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.

EchoTorch

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

easyesn

Python library for Reservoir Computing using Echo State Networks

soft-dtw-divergences

An implementation of soft-DTW divergences.

snorkel-tutorials

A collection of tutorials for Snorkel

bayesianchangepoint

An implementation of Adams & MacKay 2007 "Bayesian Online Changepoint Detection"

esrnn_torch

M4-methods

Data, Benchmarks, and methods submitted to the M4 forecasting competition

LAD

Laplacian Change Point Detection for Dynamic Graphs (KDD 2020)

BayesianTimeSeries

Bayesian Methods of Machine Learning, Skoltech 2018

text_style_transfer

Style Transfer for Texts