Guillaume Hennequin

发表

Optimal Control of Transient Dynamics in Balanced Networks Supports Generation of Complex Movements

W. Gerstner, T. Vogels, Guillaume Hennequin, 2014, Neuron.

Inhibitory Plasticity: Balance, Control, and Codependence.

Everton J. Agnes, T. Vogels, Guillaume Hennequin, 2017, Annual review of neuroscience.

iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data

Kristopher T. Jensen, Guillaume Hennequin, Marine Schimel, 2021, bioRxiv.

Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability

Guillaume Hennequin, Laurence Aitchison, Mate Lengyel, 2018, 1807.08952.

Stability and amplification in plastic cortical circuits

Guillaume Hennequin, 2013 .

Non-normal amplification in random balanced neuronal networks.

W. Gerstner, T. Vogels, Guillaume Hennequin, 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability

Guillaume Hennequin, Kenneth D. Miller, Máté Lengyel, 2018, Neuron.

Fast sampling for Bayesian inference in neural circuits

Guillaume Hennequin, Laurence Aitchison, M. Lengyel, 2014, 1404.3521.

Asymptotic scaling properties of the posterior mean and variance in the Gaussian scale mixture model

Guillaume Hennequin, Rodrigo Echeveste, M. Lengyel, 2017 .

Optimal anticipatory control as a theory of motor preparation: A thalamo-cortical circuit model

Guillaume Hennequin, Ta-Chu Kao, M. Sadabadi, 2020, Neuron.

Null Ain’t Dull: New Perspectives on Motor Cortex

Guillaume Hennequin, Ta-Chu Kao, 2018, Trends in Cognitive Sciences.

Characterizing variability in nonlinear recurrent neuronal networks

M. Lengyel, Guillaume Hennequin, 2016, 1610.03110.

icient Communication over Complex Dynamical Networks

S. Zampieri, Guillaume Hennequin, Giacomo Baggio, 2019 .

Proposals for projects: Topics in neural dynamics, information theory, and machine learning

Daniel B. Rubin, Guillaume Hennequin, Y. Ahmadian, 2019 .

Computational Explorations in Perceptual Learning

Guillaume Hennequin, 2007 .

Adaptive erasure of spurious sequences in sensory cortical circuits

M. Lengyel, Guillaume Hennequin, A. Bernacchia, 2022, Neuron.

Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector

Wulfram Gerstner, Guillaume Hennequin, Friedemann Zenke, 2013, PLoS Comput. Biol..

STDP in Adaptive Neurons Gives Close-To-Optimal Information Transmission

Jean-Pascal Pfister, Wulfram Gerstner, Guillaume Hennequin, 2010, Front. Comput. Neurosci..

Scalable Bayesian GPFA with automatic relevance determination and discrete noise models

Kristopher T. Jensen, Jasmine T. Stone, Guillaume Hennequin, 2021, bioRxiv.

Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference

Guillaume Hennequin, Máté Lengyel, Laurence Aitchison, 2019, Nature Neuroscience.

Neuroscience out of control: control-theoretic perspectives on neural circuit dynamics

Guillaume Hennequin, Ta-Chu Kao, Guillaume Hennequin, 2019, Current Opinion in Neurobiology.

Eicient Communication over Complex Dynamical Networks pdf

Giacomo Baggio, Virginia Rutten, Guillaume Hennequin, 2019 .

Stabilized supralinear network dynamics account for stimulus-induced changes of noise variability in the cortex

Guillaume Hennequin, Máté Lengyel, Yashar Ahmadian, 2016, bioRxiv.

Fast Sampling-Based Inference in Balanced Neuronal Networks

Guillaume Hennequin, Laurence Aitchison, Máté Lengyel, 2014, NIPS.

A recurrent network model of planning explains hippocampal replay and human behavior

Kristopher T. Jensen, Guillaume Hennequin, M. Mattar, 2023, bioRxiv.

Optimal anticipatory control as a theory of motor preparation: A thalamo-cortical circuit model

Guillaume Hennequin, Ta-Chu Kao, M. S. Sadabadi, 2020, Neuron.

Motor primitives in space and time via targeted gain modulation in cortical networks

Guillaume Hennequin, Mason A Porter, Tim P Vogels, 2018, Nature Neuroscience.

Exact natural gradient in deep linear networks and its application to the nonlinear case

Guillaume Hennequin, Máté Lengyel, Alberto Bernacchia, 2018, NeurIPS.

Natural continual learning: success is a journey, not (just) a destination pdf

Guillaume Hennequin, Ta-Chu Kao, Alberto Bernacchia, 2021, NeurIPS.

When and why does motor preparation arise in recurrent neural network models of motor control?

Guillaume Hennequin, Marine Schimel, Ta-Chu Kao, 2023, bioRxiv.

Manifold GPLVMs for discovering non-Euclidean latent structure in neural data pdf

Guillaume Hennequin, Ta-Chu Kao, Kristopher T. Jensen, 2020, NeurIPS.

Fisher-Legendre (FishLeg) optimization of deep neural networks

Jezabel R. Garcia, Guillaume Hennequin, A. Bernacchia, 2023, ICLR.

Non-reversible Gaussian processes for identifying latent dynamical structure in neural data

Virginia Rutten, Guillaume Hennequin, Maneesh Sahani, 2020, NeurIPS.

Efficient communication over complex dynamical networks: The role of matrix non-normality

S. Zampieri, Guillaume Hennequin, Giacomo Baggio, 2019, Science Advances.

Efficient communication over complex dynamical networks: The role of matrix non-normality.

Giacomo Baggio, Virginia Rutten, Guillaume Hennequin, 2020, Science advances.

iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data

Kristopher T. Jensen, Guillaume Hennequin, Marine Schimel, 2021, bioRxiv.

When and why does motor preparation arise in recurrent neural network models of motor control?

Guillaume Hennequin, Marine Schimel, Ta-Chu Kao, 2023, bioRxiv.

F ISHER -L EGENDRE (F ISH L EG ) OPTIMIZATION OF DEEP NEURAL NETWORKS

Jezabel R. Garcia, Guillaume Hennequin, A. Bernacchia, 2023 .

Beyond the Euclidean brain: inferring non-Euclidean latent trajectories from spike trains

Kristopher T. Jensen, M. Lengyel, Guillaume Hennequin, 2022, bioRxiv.

Neural networks subtract and conquer

Guillaume Hennequin, Guillaume Hennequin, 2017, eLife.

Analog Memories in a Balanced Rate-Based Network of E-I Neurons

Guillaume Hennequin, Máté Lengyel, Dylan Festa, 2014, NIPS.