Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

Implementation of multi-output conformal regression methods

Implementation of STVNN from the paper "Spatiotemporal Covariance Neural Networks", ECML PKDD 2024

Official implementation of "Conformal prediction for multi-dimensional time series by ellipsoidal sets" (ICML 2024 spotlight)

PyTorch implementation of the OT-Flow approach in arXiv:2006.00104

Animation engine for explanatory math videos

A community-maintained Python framework for creating mathematical animations.

Multiple-Output Quantile Regression

OpenGraphXAI collection of benchmarks for XAI in graph classification

Pytorch implementation of the Spatio-temporal GNN to cluster correlated time series

👓 A web interface of gpustat+: monitor GPU clusters at a look, with unified view of CPU and RAM load

📊+ An enhanced version of gpustat, showing also a summary of the usage of the CPU and RAM of the system.

Wes Anderson color palettes for python!

torch-molecule is a deep learning package for molecular discovery, designed with an sklearn-style interface for property prediction, inverse design and representation learning.

The library for pooling in Graph Neural Networks made for Pytorch Geometric

Official repository for the paper "Scalable Spatiotemporal Graph Neural Networks" (AAAI 2023)

Create 4chan posts with images.

Open-source implementation of AlphaEvolve

Universal markup converter

Official repository for the paper "Relational Conformal Prediction for Correlated Time Series" (ICML 2025)

Roo Code gives you a whole dev team of AI agents in your code editor.

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

🎵 A Mac app wrapper for music.youtube.com

Conformalized Quantile Regression

Information and material for the course Generative AI at UiT

Official repository of the paper "MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks" presented at ICLR 2025.

Implementation of the BNPool layer and code to reproduce the experiments in "Bayesian Nonparametric GNNs for graph pooling and clustering".

Repository for the paper "Interpreting Temporal Graph Neural Networks with Koopman Theory"