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02/14/2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
Model reparametrization – transforming the parameter space via a bijecti...
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05/07/2021
Laplace Matching for fast Approximate Inference in Generalized Linear Models
Bayesian inference in generalized linear models (GLMs), i.e. Gaussian re...
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02/12/2021
Cockpit: A Practical Debugging Tool for Training Deep Neural Networks
When engineers train deep learning models, they are very much "flying bl...
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07/30/2020
When are Neural ODE Solutions Proper ODEs?
A key appeal of the recently proposed Neural Ordinary Differential Equat...
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04/01/2020
Bayesian ODE Solvers: The Maximum A Posteriori Estimate
It has recently been established that the numerical solution of ordinary...
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02/05/2019
A Modular Approach to Block-diagonal Hessian Approximations for Second-order Optimization Methods
We propose a modular extension of the backpropagation algorithm for comp...
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07/06/2018
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
This paper is an attempt to bridge the conceptual gaps between researche...
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03/28/2017
