15 citations · 48 across the 18 of their papers we have counts for
19 papers
Dendritic structure enables powerful plasticity
Ben von Hünerbein, Federico Benitez, Kevin Max +10
Over the past decades, it has become increasingly clear that the complex morphology of cortical neurons is more than just a quirk of evolution, and that dendritic compartments serv…
On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
Christian Horvat, Jean-Pascal Pfister
Diffusion models are generative models that have recently demonstrated impressive performances in terms of sampling quality and density estimation in high dimensions. They rely on…
Rate-Distortion Problems of the Poisson Process based on a Group-Theoretic Approach
Hui-An Shen, Stefan M. Moser, Jean-Pascal Pfister
We study rate-distortion problems of a Poisson process using a group theoretic approach. By describing a realization of a Poisson point process with either point timings or inter-e…
Efficient Sampling-Based Bayesian Active Learning for synaptic characterization
Camille Gontier, Simone Carlo Surace, Igor Delvendahl +2
Bayesian Active Learning (BAL) is an efficient framework for learning the parameters of a model, in which input stimuli are selected to maximize the mutual information between the…
Density estimation on low-dimensional manifolds: an inflation-deflation approach
Christian Horvat, Jean-Pascal Pfister
Normalizing Flows (NFs) are universal density estimators based on Neural Networks. However, this universality is limited: the density's support needs to be diffeomorphic to a Eucli…
A Unification of Weighted and Unweighted Particle Filters
Ehsan Abedi, Simone Carlo Surace, Jean-Pascal Pfister
Particle filters (PFs), which are successful methods for approximating the solution of the filtering problem, can be divided into two types: weighted and unweighted PFs. It is well…