AaltoPML / spatiotemporal-graph-kernels
The official implementation of Non-separable Spatio-temporal Graph Kernels via SPDEs.
☆14Updated 2 years ago
Related projects: ⓘ
- Code of PriorVAE: encoding spatial priors with variational autoencoders☆12Updated last year
- Conformal Bayes with importance sampling☆18Updated 2 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- Course materials of "Bayesian Modelling and Probabilistic Programming" with NumPyro, initially created for "AI for Science" MSc at the Af…☆42Updated this week
- Gaussian processes on graphs and lattices in Stan and pytorch.☆14Updated 3 months ago
- "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu☆26Updated 6 years ago
- ☆11Updated 2 years ago
- Probabilistic generative model and efficient algorithm to model reciprocity in directed networks.☆16Updated 10 months ago
- ☆15Updated 3 years ago
- SIR-Hawkes: Linking Epidemic Models and Hawkes Processes to Model Diffusions in Finite Populations☆14Updated 6 years ago
- Gaussian Markov Random Fields (GMRFs) and Integrated Nested Laplace Approximation (INLA)☆18Updated 5 months ago
- Efficient, lightweight variational inference and approximation bounds☆39Updated 9 months ago
- Code accompanying the NeurIPS 2021 Paper: A Probabilistic State Space Model for Joint Inference from Differential Equations and Data (Sch…☆13Updated last year
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated last year
- A simple library to run variational inference on Stan models.☆18Updated last year
- The code in this repository follows the paper "Stochastic gradient MCMC"☆23Updated 5 years ago
- ☆20Updated last year
- Bayesian inference for a logistic regression model in various languages☆43Updated last year
- Tools for generalized quantile modeling☆14Updated last year
- Home for the book-in-progress 'Bayesian Learning'☆27Updated last week
- Quantifying and reporting uncertainty in drug discovery predictions with probabilistic models☆11Updated 2 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆21Updated 11 months ago
- This tutorial is a basic guide to understanding the Zig-Zag Sampling method. This document is released with the aim of diffusion and shar…☆18Updated 5 years ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- Sampling with Blackjax on Aesara☆11Updated last year
- ☆7Updated 6 months ago
- Bayesian inference and posterior analysis for Python☆41Updated 9 months ago
- Code and data for the manuscript "Optimal, near-optimal, and robust epidemic control"☆11Updated 2 years ago
- Computational statistics and machine learning reading group at Imperial College London (2019-2020)☆23Updated 3 months ago
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆20Updated last month