Methods and Applications in Biomedicine
I defended my PhD! Neural optimal transport for biomedicine? A overview below with the thesis highlights.
The full thesis is available for download here.
|This thesis develops machine learning methods for modeling dynamical systems. Central application: drug discovery and single-cell biology with the aim to predict single cell responses to perturbations such as drugs. Challenge: We cannot trace the response of individual cells.|
|To achieve this, this thesis connects a variety of seemingly unrelated concepts into a unified framework: We propose #neural optimal transport methods that can be parameterized through static maps or dynamic ODEs, SDEs, PDEs. See also our ICML 2023 tutorial for a deep dive!|
|The first method, |
Have a look at our Research Briefing in Nature Methods and the feature in ETH Press
|Moving beyond such static formulations, we explore OT's connections to dynamical systems theory. The result is |
|Lastly, building on SDE theory, diffusion models, and flow matching, |