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. However, it is...

The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!

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 a principled framewo...

Jaxley is a versatile platform for biophysical modeling in neuroscience. It allows efficiently simulating large-scale biophysical models on CPUs, GPUs and TPUs. Model parameters can be optimized with ...

Instead, neurons encode the position of sequential items in working memory based on when they fire during ongoing brain wave oscillations—a finding that challenges a long-standing theory.

Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers - Volume 71

The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!

Amortized simulation-based inference (SBI) methods train neural networks on simulated data to perform Bayesian inference. While this strategy avoids the need for tractable likelihoods, it often requir...

Schulz et al. demonstrate how neural encoding and decoding can be cast as computing conditional distributions and how to modify variational autoencoders (VAEs) to calculate such distributions. The pro...

The temporal order of events in working memory is thought to be reflected by ordered neuronal firing at different phases. Here the authors show that this is not the case and that phase order is linked...

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 significant challeng...

The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!