11 citations · 17 across the 5 of their papers we have counts for
7 papers
Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging
Özgün Turgut, Philip Müller, Paul Hager +5
Cardiovascular diseases (CVD) can be diagnosed using various diagnostic modalities. The electrocardiogram (ECG) is a cost-effective and widely available diagnostic aid that provide…
Best of Both Worlds: Multimodal Contrastive Learning with Tabular and Imaging Data
Paul Hager, Martin J. Menten, Daniel Rueckert
Medical datasets and especially biobanks, often contain extensive tabular data with rich clinical information in addition to images. In practice, clinicians typically have less dat…
Optimal stopping with signatures
Christian Bayer, Paul Hager, Sebastian Riedel +1
We propose a new method for solving optimal stopping problems (such as American option pricing in finance) under minimal assumptions on the underlying stochastic process . We co…
Unified Signature Cumulants and Generalized Magnus Expansions
Peter K. Friz, Paul Hager, Nikolas Tapia
The signature of a path can be described as its full non-commutative exponential. Following T. Lyons we regard its expectation, the expected signature, as path space analogue of th…
Reinforced optimal control
Christian Bayer, Denis Belomestny, Paul Hager +3
Least squares Monte Carlo methods are a popular numerical approximation method for solving stochastic control problems. Based on dynamic programming, their key feature is the appro…
The Multiplicative Chaos of Fractional Brownian Fields
Paul Hager, Eyal Neuman
We consider a family of fractional Brownian fields on , where denotes their Hurst parameter. We first define a rich class of normalizin…
Randomized optimal stopping algorithms and their convergence analysis
Christian Bayer, Denis Belomestny, Paul Hager +2
In this paper we study randomized optimal stopping problems and consider corresponding forward and backward Monte Carlo based optimisation algorithms. In particular we prove the co…