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Sparse Physics-based and Interpretable Neural Networks
Probabilistic Numerical Method of Lines (PNMOL): Implementation and Experiments
Implements Inside-Out SMC^2, a nested sequential Monte Carlo algorithm developed for Bayesian experimental design in dynamical systems.
Second-order iterated smoothing algorithms for state estimation
A template repo for Python packages
Must-read Papers on Physics-Informed Neural Networks.
A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algorithms, both in a sequential and parallel fashion, as well a…
Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"
A Quarto extension to embed PDF files in HTML formats
GPU Programming with Julia 2023 - course at the Swiss National Supercomputing Centre (CSCS), ETH Zurich
A zoo of implementations of differential equation problems in NumPy and JAX. Oscillators, chemical reactions, n-body problems, epidemiological models, IVPs, BVPs, and more.
Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.
Source code that accompanies The CUDA Handbook.
Code from the "CUDA Crash Course" YouTube series by CoffeeBeforeArch
Get started with CUDA programming
Quarto extension for Computo template
Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
This package implements the methods described in https://arxiv.org/abs/2004.14455 for fast Gaussian process statistics
Demonstrations of Gaussian processes for computation, inference and uncertainty quantification with PDE measurements
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
Official Implementation of Constrained Neural Fields (CNF)
A new markup-based typesetting system that is powerful and easy to learn.