4 citations · 8 across the 8 of their papers we have counts for
9 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…
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…
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…
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…
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…
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…
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation
Richard Gao, Michael Deistler, Jakob H. Macke
Simulation-based inference (SBI) enables amortized Bayesian inference for simulators with implicit likelihoods. But when we are primarily interested in the quality of predictive si…
SoK: Vehicle Orientation Representations for Deep Rotation Estimation
Huahong Tu, Siyuan Peng, Vladimir Leung +1
In recent years, there is an influx of deep learning models for 3D vehicle object detection. However, little attention was paid to orientation prediction. Existing research work pr…
Systematic benchmarking of HTTPS third party copy on 100Gbps links using XRootD
Edgar Fajardo, Aashay Arora, Diego Davila +3
The High Luminosity Large Hadron Collider provides a data challenge. The amount of data recorded from the experiments and transported to hundreds of sites will see a thirty fold in…