6 papers
stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation
Lucas Maes, Quentin Le Lidec, Luiz Facury +9
World models are central to building agents that can reason, plan, and generalize beyond their training data. However, research on world models is currently fragmented, with dispar…
Neural timescales from a computational perspective
Roxana Zeraati, Anna Levina, Jakob H. Macke +1
Neural activity fluctuates over a wide range of timescales within and across brain areas. Experimental observations suggest that diverse neural timescales reflect information in dy…
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…
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…
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation
Julius Vetter, Guy Moss, Cornelius Schröder +2
Scientific modeling applications often require estimating a distribution of parameters consistent with a dataset of observations - an inference task also known as source distributi…
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…