collaborators

5 papers

eess.IV2025

MRExtrap: Longitudinal Aging of Brain MRIs using Linear Modeling in Latent Space

Jaivardhan Kapoor, Jakob H. Macke, Christian F. Baumgartner

Simulating aging in 3D brain MRI scans can reveal disease progression patterns in neurological disorders such as Alzheimer's disease. Current deep learning-based generative models…

cs.LG2025

EDAPT: Towards Calibration-Free BCIs with Continual Online Adaptation

Lisa Haxel, Jaivardhan Kapoor, Ulf Ziemann +1

Brain-computer interfaces (BCIs) suffer from accuracy degradation as neural signals drift over time and vary across users, requiring frequent recalibration that limits practical de…

cs.LG2025

sbi reloaded: a toolkit for simulation-based inference workflows

Jan Boelts, Michael Deistler, Manuel Gloeckler +30

Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a…

q-bio.NC2024

Latent Diffusion for Neural Spiking Data

Jaivardhan Kapoor, Auguste Schulz, Julius Vetter +3

Modern datasets in neuroscience enable unprecedented inquiries into the relationship between complex behaviors and the activity of many simultaneously recorded neurons. While laten…

cs.LG2024

A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Science

Sebastian Bischoff, Alana Darcher, Michael Deistler +18

Generative models are invaluable in many fields of science because of their ability to capture high-dimensional and complicated distributions, such as photo-realistic images, prote…