research
∙
08/02/2022
Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs
Neural operators are a type of deep architecture that learns to solve (i...
share
research
∙
12/03/2021
ProbNum: Probabilistic Numerics in Python
Probabilistic numerical methods (PNMs) solve numerical problems via prob...
research
∙
10/22/2021
Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations
This work develops a class of probabilistic algorithms for the numerical...
research
∙
10/22/2021
Probabilistic ODE Solutions in Millions of Dimensions
Probabilistic solvers for ordinary differential equations (ODEs) have em...
research
∙
06/14/2021
Linear-Time Probabilistic Solutions of Boundary Value Problems
We propose a fast algorithm for the probabilistic solution of boundary v...
research
∙
03/18/2021
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data
Mechanistic models with differential equations are a key component of sc...
research
∙
12/18/2020
Stable Implementation of Probabilistic ODE Solvers
Probabilistic solvers for ordinary differential equations (ODEs) provide...
research
∙
02/21/2020