4 citations · 5 across the 4 of their papers we have counts for
9 papers
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…
Simulation-Based Inference: A Practical Guide
Michael Deistler, Jan Boelts, Peter Steinbach +11
A central challenge in many areas of science and engineering is to identify model parameters that are consistent with prior knowledge and empirical data. Bayesian inference offers…
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…
Learning Individual Reproductive Behavior from Aggregate Fertility Rates via Neural Posterior Estimation
Daniel Ciganda, Ignacio Campón, Iñaki Permanyer +1
Age-specific fertility rates (ASFRs) provide the most extensive record of reproductive change, but their aggregate nature obscures the individual-level behavioral mechanisms that d…
Identifying multi-compartment Hodgkin-Huxley models with high-density extracellular voltage recordings
Ian Christopher Tanoh, Michael Deistler, Jakob H. Macke +1
Multi-compartment Hodgkin-Huxley models are biophysical models of how electrical signals propagate throughout a neuron, and they form the basis of our knowledge of neural computati…
FNOPE: Simulation-based inference on function spaces with Fourier Neural Operators
Guy Moss, Leah Sophie Muhle, Reinhard Drews +2
Simulation-based inference (SBI) is an established approach for performing Bayesian inference on scientific simulators. SBI so far works best on low-dimensional parametric models.…