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06/13/2023
Differentiating Metropolis-Hastings to Optimize Intractable Densities
We develop an algorithm for automatic differentiation of Metropolis-Hast...
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06/12/2023
Extending JumpProcess.jl for fast point process simulation with time-varying intensities
Point processes model the occurrence of a countable number of random poi...
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04/13/2023
Automated Translation and Accelerated Solving of Differential Equations on Multiple GPU Platforms
We demonstrate a high-performance vendor-agnostic method for massively p...
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07/17/2022
Parallelizing Explicit and Implicit Extrapolation Methods for Ordinary Differential Equations
Numerically solving ordinary differential equations (ODEs) is a naturall...
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04/19/2022
Plots.jl – a user extendable plotting API for the julia programming language
There are plenty of excellent plotting libraries. Each excels at a diffe...
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01/28/2022
Mixing Implicit and Explicit Deep Learning with Skip DEQs and Infinite Time Neural ODEs (Continuous DEQs)
Implicit deep learning architectures, like Neural ODEs and Deep Equilibr...
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05/09/2021
High-performance symbolic-numerics via multiple dispatch
As mathematical computing becomes more democratized in high-level langua...
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05/09/2021
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics
Democratization of machine learning requires architectures that automati...
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03/29/2021
Stiff Neural Ordinary Differential Equations
Neural Ordinary Differential Equations (ODE) are a promising approach to...
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01/13/2020
Universal Differential Equations for Scientific Machine Learning
In the context of science, the well-known adage "a picture is worth a th...
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12/05/2018
A Comparison of Automatic Differentiation and Continuous Sensitivity Analysis for Derivatives of Differential Equation Solutions
The derivatives of differential equation solutions are commonly used as ...
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07/17/2018