shchur

autogluon

Fast and Accurate ML in 3 Lines of Code

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

automlbenchmark

OpenML AutoML Benchmarking Framework

gnn-benchmark

Framework for evaluating Graph Neural Network models on semi-supervised node classification task

ifl-tpp

Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)

overlapping-community-detection

Implementation of "Overlapping Community Detection with Graph Neural Networks"

shchur.github.io

survival_distributions

Extended functionality for univariate probability distributions in PyTorch

tpp-anomaly-detection

Implementation of "Detecting Anomalous Event Sequences with Temporal Point Processes" (NeurIPS 2021)

triangular-tpp

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

shchur/gnn-benchmark

Framework for evaluating Graph Neural Network models on semi-supervised node classification task

shchur/overlapping-community-detection

Implementation of "Overlapping Community Detection with Graph Neural Networks"

shchur/ifl-tpp

Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)

shchur/tpp-anomaly-detection

Implementation of "Detecting Anomalous Event Sequences with Temporal Point Processes" (NeurIPS 2021)

shchur/triangular-tpp

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

shchur/survival_distributions

Extended functionality for univariate probability distributions in PyTorch

shchur/automlbenchmark

OpenML AutoML Benchmarking Framework

shchur/shchur.github.io

shchur/Auto-PyTorch

Automatic architecture search and hyperparameter optimization for PyTorch

shchur/autogluon

AutoGluon: AutoML for Image, Text, and Tabular Data

shchur/autogluon-cloud

Autogluon-cloud aims to provide user tools to train, fine-tune and deploy AutoGluon backed models on the cloud. With just a few lines of codes, users could train a model and perform inference on the cloud without worrying about MLOps details such as resource management

shchur/autogluon-doc-utils

shchur/gluonts

Probabilistic time series modeling in Python

shchur/sktime

A unified framework for machine learning with time series

shchur/hydra

Hydra is a framework for elegantly configuring complex applications

shchur/nixtla

Python SDK for TimeGPT, a foundational time series model

shchur/tabrepo

shchur/tsbench