Search Results - "Surace, Simone Carlo"
-
1
Learning as filtering: Implications for spike-based plasticity
Published in PLoS computational biology (23-02-2022)“…Most normative models in computational neuroscience describe the task of learning as the optimisation of a cost function with respect to a set of parameters…”
Get full text
Journal Article -
2
Online Maximum-Likelihood Estimation of the Parameters of Partially Observed Diffusion Processes
Published in IEEE transactions on automatic control (01-07-2019)“…We revisit the problem of estimating the parameters of a partially observed diffusion process, consisting of a hidden state process and an observed process,…”
Get full text
Journal Article -
3
On the choice of metric in gradient-based theories of brain function
Published in PLoS computational biology (01-04-2020)“…This is a PLOS Computational Biology Education paper. The idea that the brain functions so as to minimize certain costs pervades theoretical neuroscience…”
Get full text
Journal Article -
4
Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception
Published in Scientific reports (18-08-2017)“…The robust estimation of dynamical hidden features, such as the position of prey, based on sensory inputs is one of the hallmarks of perception. This dynamical…”
Get full text
Journal Article -
5
Efficient sampling-based Bayesian Active Learning for synaptic characterization
Published in PLoS computational biology (01-08-2023)“…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…”
Get full text
Journal Article -
6
A Statistical Model for In Vivo Neuronal Dynamics
Published in PloS one (16-11-2015)“…Single neuron models have a long tradition in computational neuroscience. Detailed biophysical models such as the Hodgkin-Huxley model as well as simplified…”
Get full text
Journal Article -
7
Learning as filtering: Implications for spike-based plasticity
Published in PLoS computational biology (01-02-2022)“…Most normative models in computational neuroscience describe the task of learning as the optimisation of a cost function with respect to a set of parameters…”
Get full text
Journal Article -
8
The Hitchhiker’s guide to nonlinear filtering
Published in Journal of mathematical psychology (01-02-2020)“…Nonlinear filtering is used in online estimation of a dynamic hidden variable from incoming data and has vast applications in different fields, ranging from…”
Get full text
Journal Article -
9
Publisher Correction: Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception
Published in Scientific reports (11-12-2017)“…A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper…”
Get full text
Journal Article -
10
Asymptotically Exact Unweighted Particle Filter for Manifold-Valued Hidden States and Point Process Observations
Published in IEEE control systems letters (01-04-2020)“…The filtering of a Markov diffusion process on a manifold from counting process observations leads to `large' changes in the conditional distribution upon an…”
Get full text
Journal Article -
11
A Statistical Model for In Vivo Neuronal Dynamics: e0142435
Published in PloS one (01-11-2015)“…Single neuron models have a long tradition in computational neuroscience. Detailed biophysical models such as the Hodgkin-Huxley model as well as simplified…”
Get full text
Journal Article -
12
Gauge Freedom within the Class of Linear Feedback Particle Filters
Published in 2019 IEEE 58th Conference on Decision and Control (CDC) (01-12-2019)“…Feedback particle filters (FPFs) are Monte-Carlo approximations of the solution of the filtering problem in continuous time. The samples or particles evolve…”
Get full text
Conference Proceeding -
13
Gauge Freedom within the Class of Linear Feedback Particle Filters
Published 15-03-2019“…Feedback particle filters (FPFs) are Monte-Carlo approximations of the solution of the filtering problem in continuous time. The samples or particles evolve…”
Get full text
Journal Article -
14
A Unification of Weighted and Unweighted Particle Filters
Published 12-03-2022“…SIAM Journal on Control and Optimization, Volume 60, Issue 2, pp. 597-619 (2022) Particle filters (PFs), which are successful methods for approximating the…”
Get full text
Journal Article -
15
Efficient Sampling-Based Bayesian Active Learning for synaptic characterization
Published 19-01-2022“…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…”
Get full text
Journal Article -
16
Asymptotically exact unweighted particle filter for manifold-valued hidden states and point process observations
Published 23-07-2019“…The filtering of a Markov diffusion process on a manifold from counting process observations leads to `large' changes in the conditional distribution upon an…”
Get full text
Journal Article -
17
The Hitchhiker's Guide to Nonlinear Filtering
Published 21-03-2019“…Nonlinear filtering is the problem of online estimation of a dynamic hidden variable from incoming data and has vast applications in different fields, ranging…”
Get full text
Journal Article -
18
Online Maximum Likelihood Estimation of the Parameters of Partially Observed Diffusion Processes
Published 01-11-2016“…We revisit the problem of estimating the parameters of a partially observed diffusion process, consisting of a hidden state process and an observed process,…”
Get full text
Journal Article -
19
On the choice of metric in gradient-based theories of brain function
Published 30-05-2018“…The idea that the brain functions so as to minimize certain costs pervades theoretical neuroscience. Since a cost function by itself does not predict how the…”
Get full text
Journal Article -
20
A statistical model for in vivo neuronal dynamics
Published 23-10-2015“…Single neuron models have a long tradition in computational neuroscience. Detailed biophysical models such as the Hodgkin-Huxley model as well as simplified…”
Get full text
Journal Article