58 citations · 136 across the 13 of their papers we have counts for
6 papers · 1 filter
Interacting particle solutions of Fokker-Planck equations through gradient-log-density estimation
Dimitra Maoutsa, Sebastian Reich, Manfred Opper
Fokker-Planck equations are extensively employed in various scientific fields as they characterise the behaviour of stochastic systems at the level of probability density functions…
GP-ETAS: Semiparametric Bayesian inference for the spatio-temporal Epidemic Type Aftershock Sequence model
Christian Molkenthin, Christian Donner, Sebastian Reich +4
The spatio-temporal Epidemic Type Aftershock Sequence (ETAS) model is widely used to describe the self-exciting nature of earthquake occurrences. While traditional inference method…
A Dynamical Mean-Field Theory for Learning in Restricted Boltzmann Machines
Burak Çakmak, Manfred Opper
We define a message-passing algorithm for computing magnetizations in Restricted Boltzmann machines, which are Ising models on bipartite graphs introduced as neural network models…
A Mathematical Model of Local and Global Attention in Natural Scene Viewing
Noa Malem-Shinitski, Manfred Opper, Sebastian Reich +3
Understanding the decision process underlying gaze control is an important question in cognitive neuroscience with applications in diverse fields ranging from psychology to compute…
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models
Théo Galy-Fajou, Florian Wenzel, Manfred Opper
We propose automated augmented conjugate inference, a new inference method for non-conjugate Gaussian processes (GP) models. Our method automatically constructs an auxiliary variab…
Analysis of Bayesian Inference Algorithms by the Dynamical Functional Approach
Burak Çakmak, Manfred Opper
We analyze the dynamics of an algorithm for approximate inference with large Gaussian latent variable models in a student-teacher scenario. To model nontrivial dependencies between…