Build high-quality Laplace matrices on meshes and point clouds in Python. Implements [Sharp & Crane SGP 2020].

Tools for diffing and merging of Jupyter notebooks.

Laplace approximations for Deep Learning.

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Distance-based Analysis of DAta-manifolds in python

📒 Sphinx source parser for Jupyter notebooks

A clean customizable documentation theme for Sphinx

A robust Laplace matrix for general (possibly nonmanifold) triangle meshes, and point clouds [Sharp & Crane SGP 2020]

High-quality QR Code generator library in Java, TypeScript/JavaScript, Python, Rust, C , C.

A new approach to API documentation in Sphinx.

A Bayesian optimization toolbox built on TensorFlow

Code for the paper "Intrinsic Gaussian Vector Fields on Manifolds" by Robert-Nicoud, Krause, and Borovitskiy

pytest plugin for distributed testing and loop-on-failures testing modes.

Multiple dispatch in Python

📝 Pytest plugin for testing notebooks

Computations and statistics on manifolds with geometric structures.

Repository containing the code for Implicit Manifold Gaussian Process.

Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces

Chrome/Firefox extension that blocks access to distracting websites to improve your productivity.

Bayesian optimization in PyTorch

Gaussian processes in JAX.

NASLib is a Neural Architecture Search (NAS) library for facilitating NAS research for the community by providing interfaces to several state-of-the-art NAS search spaces and optimizers.

Isotropic Gaussian Processs on Finite Spaces of Graphs (AISTATS 2023)

Isotropic Gaussian Processs on Finite Spaces of Graphs (AISTATS 2023)

Fast computation of diffusion maps and geometric harmonics in Python. Moved to https://git.sr.ht/~jmbr/diffusion-maps

Fast Convergence of Conjugate Gradients in Sparse Gaussian Processes

A scikit-learn compatible library for graph kernels