Jean-Pascal Pfister

41 papers A* 3B 4C 1Journal 26Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
Capacity-Achieving Input Distribution of the Additive Uniform Noise Channel With Peak Amplitude and Cost Constraint.
CoRR
Jonas Stapmanns, Catarina Dias, Luke Eilers, Jean-Pascal Pfister
2025 B conf
Capacity-Achieving Input Distribution of the Additive Uniform Noise Channel with Peak Amplitude and Cost Constraint.
ISIT
Jonas Stapmanns, Catarina Dias, Luke Eilers, Jean-Pascal Pfister
2025 J jnl
On the stability of event-based control with neuronal dynamics.
CoRR
Luke Eilers, Jonas Stapmanns, Catarina Dias, Jean-Pascal Pfister
2025 J jnl
Phase Transitions of the Additive Uniform Noise Channel with Peak Amplitude and Cost Constraint.
CoRR
Jonas Stapmanns, Catarina Dias, Luke Eilers, Tobias Kühn, Jean-Pascal Pfister
2024 A* conf
On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models.
ICLR
Christian Horvat, Jean-Pascal Pfister
2024 J jnl
On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models.
CoRR
Christian Horvat, Jean-Pascal Pfister
2024 — conf
Optimal Activation Functions via Causal Wyner-Ziv Coding.
ISIT (Workshops)
Hui-An Shen, Jean-Pascal Pfister, Robert Graczyk
2023 B conf
A Generalization of the Equal Coding Theorem.
ITW
Hui-An Shen, Stefan M. Moser, Jean-Pascal Pfister
2023 J jnl
Density estimation on low-dimensional manifolds: an inflation-deflation approach.
J. Mach. Learn. Res.
Christian Horvat, Jean-Pascal Pfister
2023 J jnl
Efficient sampling-based Bayesian Active Learning for synaptic characterization.
PLoS Comput. Biol.
Camille Gontier, Simone Carlo Surace, Igor Delvendahl, Martin Müller, Jean-Pascal Pfister
2022 J jnl
A Unification of Weighted and Unweighted Particle Filters.
SIAM J. Control. Optim.
Ehsan Abedi, Simone Carlo Surace, Jean-Pascal Pfister
2022 J jnl
Correction: Bayesian regression explains how human participants handle parameter uncertainty.
PLoS Comput. Biol.
Jannes Jegminat, Maya A. Jastrzebowska, Matthew V. Pachai, Michael H. Herzog, Jean-Pascal Pfister
2022 A* conf
Intrinsic dimensionality estimation using Normalizing Flows.
NeurIPS
Christian Horvat, Jean-Pascal Pfister
2022 J jnl
Learning as filtering: Implications for spike-based plasticity.
PLoS Comput. Biol.
Jannes Jegminat, Simone Carlo Surace, Jean-Pascal Pfister
2022 J jnl
Rate-Distortion Problems of the Poisson Process based on a Group-Theoretic Approach.
CoRR
Hui-An Shen, Stefan M. Moser, Jean-Pascal Pfister
2021 A* conf
Denoising Normalizing Flow.
NeurIPS
Christian Horvat, Jean-Pascal Pfister
2021 J jnl
Density estimation: an inflation-deflation approach.
CoRR
Christian Horvat, Jean-Pascal Pfister
2021 B conf
Rate-Distortion Problems of the Poisson Process: a Group-Theoretic Approach.
ITW
Hui-An Shen, Stefan M. Moser, Jean-Pascal Pfister
2020 J jnl
A Unification of Weighted and Unweighted Particle Filters.
CoRR
Ehsan Abedi, Simone Carlo Surace, Jean-Pascal Pfister
2020 J jnl
Asymptotically Exact Unweighted Particle Filter for Manifold-Valued Hidden States and Point Process Observations.
IEEE Control. Syst. Lett.
Simone Carlo Surace, Anna Kutschireiter, Jean-Pascal Pfister
2020 J jnl
Bayesian regression explains how human participants handle parameter uncertainty.
PLoS Comput. Biol.
Jannes Jegminat, Maya A. Jastrzebowska, Matthew V. Pachai, Michael H. Herzog, Jean-Pascal Pfister
2020 J jnl
Identifiability of a Binomial Synapse.
Frontiers Comput. Neurosci.
Camille Gontier, Jean-Pascal Pfister
2020 J jnl
On the choice of metric in gradient-based theories of brain function.
PLoS Comput. Biol.
Simone Carlo Surace, Jean-Pascal Pfister, Wulfram Gerstner, Johanni Brea
2020 J jnl
Propagation of Spiking Moments in Linear Hawkes Networks.
SIAM J. Appl. Dyn. Syst.
Matthieu Gilson, Jean-Pascal Pfister
2020 B conf
Sphere Covering for Poisson Processes.
ITW
Hui-An Shen, Stefan M. Moser, Jean-Pascal Pfister
2019 J jnl
How to Avoid the Curse of Dimensionality: Scalability of Particle Filters with and without Importance Weights.
SIAM Rev.
Simone Carlo Surace, Anna Kutschireiter, Jean-Pascal Pfister
2019 J jnl
Online Maximum-Likelihood Estimation of the Parameters of Partially Observed Diffusion Processes.
IEEE Trans. Autom. Control.
Simone Carlo Surace, Jean-Pascal Pfister
2018 J jnl
Propagation of moments in Hawkes networks.
CoRR
Matthieu Gilson, Jean-Pascal Pfister
2017 J jnl
Optimised information gathering in smartphone users.
CoRR
Arko Ghosh, Jean-Pascal Pfister, Matthew Cook
2016 J jnl
Quantifying the priority placed on scale-free smartphone actions.
CoRR
Jean-Pascal Pfister, Arko Ghosh
2014 — ch.
Reinforcement Learning in Cortical Networks.
Encyclopedia of Computational Neuroscience
Walter Senn, Jean-Pascal Pfister
2014 — ch.
Spike-Timing-Dependent Plasticity, Learning Rules.
Encyclopedia of Computational Neuroscience
Walter Senn, Jean-Pascal Pfister
2011 — conf
Sequence learning with hidden units in spiking neural networks.
NIPS
Johanni Brea, Walter Senn, Jean-Pascal Pfister
2010 J jnl
STDP in Adaptive Neurons Gives Close-To-Optimal Information Transmission.
Frontiers Comput. Neurosci.
Guillaume Hennequin, Wulfram Gerstner, Jean-Pascal Pfister
2010 J jnl
STDP in Oscillatory Recurrent Networks: Theoretical Conditions for Desynchronization and Applications to Deep Brain Stimulation.
Frontiers Comput. Neurosci.
Jean-Pascal Pfister, Peter A. Tass
2009 — conf
Know Thy Neighbour: A Normative Theory of Synaptic Depression.
NIPS
Jean-Pascal Pfister, Peter Dayan, Máté Lengyel
2007 J jnl
Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution.
Neural Comput.
Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner
2006 J jnl
Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning.
Neural Comput.
Jean-Pascal Pfister, Taro Toyoizumi, David Barber, Wulfram Gerstner
2005 — conf
Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects.
NIPS
Jean-Pascal Pfister, Wulfram Gerstner
2004 — conf
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model.
NIPS
Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner
2003 C conf
Optimal Hebbian Learning: A Probabilistic Point of View.
ICANN
Jean-Pascal Pfister, David Barber, Wulfram Gerstner