aniketjivani

PytorchGeometricTutorial

Pytorch Geometric Tutorials

SpeedyWeather.jl

Play atmospheric modelling like it's LEGO.

MPE24

Material for minitutorial at SIAM-MPE24

STRbook

Supplementary package for "Spatio-Temporal Statistics with R" by C.K. Wikle, A. Zammit-Mangion, and N. Cressie

CyCNN

CVAE_MNIST

Conditional VAE using CNN on MNIST in PyTorch

statsmodels

Statsmodels: statistical modeling and econometrics in Python

dm_hamiltonian_dynamics_suite

MassSpringDamper_Env

uni2ts

[ICML2024] Unified Training of Universal Time Series Forecasting Transformers

riemann_book

An interactive book about the Riemann problem for hyperbolic PDEs, using Jupyter notebooks.

formula1-telemetry-tool

A fast, GUI based application, providing insight into Formula 1 telemetry data.

pyclaw

PyClaw is a Python-based interface to the algorithms of Clawpack and SharpClaw. It also contains the PetClaw package, which adds parallelism through PETSc.

Code4CFD

A curated list of repositories related to fluid dynamics.

ADE-python

Finite volume based solver for Advection-Diffusion Equation solver using only Python

data-driven-advection

LaSDI

numerical-analysis-mathematical-neuroscience

This is material written for the masterclass Numerical and Analytical Methods for Spatially-Extended Neurobiological Networks, held at the Centre for Complex Systems Studies, University of Utrecht in May 2024.

random-fourier-features

Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model

DeepKoopman

neural networks to learn Koopman eigenfunctions

NeuralCDE

Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

sci-comp-notebooks

A collection of scientific computing notebooks

BayesianOptimization

A Python implementation of global optimization with gaussian processes.

Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

lag-llama

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

dissipative_hnns

Training neural networks to disentangle conservative and dissipative dynamics

posteriors

Uncertainty quantification with PyTorch

jacobian_free_backprop

Implicit networks can be trained efficiently and simply by using Jacobian-free Backprop (JFB).

Operation-level-FI

breadboard

A library for prototyping generative AI applications.