Jean-Pascal Pfister

Orcid: 0000-0002-1847-3389

According to our database1, Jean-Pascal Pfister authored at least 35 papers between 2003 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Optimal Activation Functions via Causal Wyner-Ziv Coding.
Proceedings of the IEEE International Symposium on Information Theory, 2024

On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Efficient sampling-based Bayesian Active Learning for synaptic characterization.
PLoS Comput. Biol., 2023

Density estimation on low-dimensional manifolds: an inflation-deflation approach.
J. Mach. Learn. Res., 2023

A Generalization of the Equal Coding Theorem.
Proceedings of the IEEE Information Theory Workshop, 2023

2022
A Unification of Weighted and Unweighted Particle Filters.
SIAM J. Control. Optim., 2022

Learning as filtering: Implications for spike-based plasticity.
PLoS Comput. Biol., 2022

Correction: Bayesian regression explains how human participants handle parameter uncertainty.
PLoS Comput. Biol., 2022

Rate-Distortion Problems of the Poisson Process based on a Group-Theoretic Approach.
CoRR, 2022

Intrinsic dimensionality estimation using Normalizing Flows.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Density estimation: an inflation-deflation approach.
CoRR, 2021

Denoising Normalizing Flow.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Rate-Distortion Problems of the Poisson Process: a Group-Theoretic Approach.
Proceedings of the IEEE Information Theory Workshop, 2021

2020
Propagation of Spiking Moments in Linear Hawkes Networks.
SIAM J. Appl. Dyn. Syst., 2020

On the choice of metric in gradient-based theories of brain function.
PLoS Comput. Biol., 2020

Bayesian regression explains how human participants handle parameter uncertainty.
PLoS Comput. Biol., 2020

Identifiability of a Binomial Synapse.
Frontiers Comput. Neurosci., 2020

Asymptotically Exact Unweighted Particle Filter for Manifold-Valued Hidden States and Point Process Observations.
IEEE Control. Syst. Lett., 2020

Sphere Covering for Poisson Processes.
Proceedings of the IEEE Information Theory Workshop, 2020

2019
Online Maximum-Likelihood Estimation of the Parameters of Partially Observed Diffusion Processes.
IEEE Trans. Autom. Control., 2019

How to Avoid the Curse of Dimensionality: Scalability of Particle Filters with and without Importance Weights.
SIAM Rev., 2019

2018
Propagation of moments in Hawkes networks.
CoRR, 2018

2017
Optimised information gathering in smartphone users.
CoRR, 2017

2016
Quantifying the priority placed on scale-free smartphone actions.
CoRR, 2016

2014
Spike-Timing-Dependent Plasticity, Learning Rules.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Reinforcement Learning in Cortical Networks.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

2011
Sequence learning with hidden units in spiking neural networks.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
STDP in Oscillatory Recurrent Networks: Theoretical Conditions for Desynchronization and Applications to Deep Brain Stimulation.
Frontiers Comput. Neurosci., 2010

STDP in Adaptive Neurons Gives Close-To-Optimal Information Transmission.
Frontiers Comput. Neurosci., 2010

2009
Know Thy Neighbour: A Normative Theory of Synaptic Depression.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007
Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution.
Neural Comput., 2007

2006
Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning.
Neural Comput., 2006

2005
Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Optimal Hebbian Learning: A Probabilistic Point of View.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003


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