5 citations · 19 across the 15 of their papers we have counts for
4 papers · 1 filter
Learning Hybrid Biophysical Neuron Models with Neural ODEs
Jonas Beck, Michael Deistler, Dóra Viktória Molnár +2
Biophysical neuron models link measurements of neural activity to underlying cellular mechanisms. Yet, a central challenge is that the kinetics of many ion channels are poorly char…
Mixed neural posterior estimation for simulators with discrete and continuous parameters
Jan Boelts, Cornelius Schröder, Jonas Beck +3
Neural Posterior Estimation (NPE) enables rapid parameter inference for complex simulators with intractable likelihoods. NPE trains an inference network to estimate a probability d…
Scalable Simulation-Based Model Inference with Test-Time Complexity Control
Manuel Gloeckler, J. P. Manzano-Patrón, Stamatios N. Sotiropoulos +2
Simulation plays a central role in scientific discovery. In many applications, the bottleneck is no longer running a simulator; it is choosing among large families of plausible sim…
A Probabilistic Framework for LLM-Based Model Discovery
Stefan Wahl, Raphaela Schenk, Ali Farnoud +2
Automated methods for discovering mechanistic simulator models from observational data offer a promising path toward accelerating scientific progress. Such methods often take the f…