Guillaume Hennequin

According to our database, Guillaume Hennequin authored at least 20 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Efficient Model Compression Techniques with FishLeg.

Jamie McGowan, Wei Sheng Lai, Weibin Chen, Henry Aldridge, Jools Clarke, Jezabel Garcia, Rui Xia, Yilei Liang, Guillaume Hennequin, Alberto Bernacchia

CoRR, 2024

Second-order forward-mode optimization of recurrent neural networks for neuroscience.

Youjing Yu, Rui Xia, Qingxi Ma, Máté Lengyel, Guillaume Hennequin

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization.

Davide Buffelli, Jamie McGowan, Wangkun Xu, Alexandru Cioba, Da-shan Shiu, Guillaume Hennequin, Alberto Bernacchia

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Learning interpretable control inputs and dynamics underlying animal locomotion.

Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin, Christian K. Machens, Michael B. Orger, Adrien Jouary

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Fisher-Legendre (FishLeg) optimization of deep neural networks.

Jezabel R. Garcia, Federica Freddi, Stathi Fotiadis, Maolin Li, Sattar Vakili, Alberto Bernacchia, Guillaume Hennequin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

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

Marine Schimel, Ta-Chu Kao, Kristopher T. Jensen, Guillaume Hennequin

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

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

Ta-Chu Kao, Kristopher T. Jensen, Alberto Bernacchia, Guillaume Hennequin

CoRR, 2021

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

Ta-Chu Kao, Kristopher T. Jensen, Gido van de Ven, Alberto Bernacchia, Guillaume Hennequin

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

Scalable Bayesian GPFA with automatic relevance determination and discrete noise models.

Kristopher T. Jensen, Ta-Chu Kao, Jasmine Stone, Guillaume Hennequin

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

2020

Automatic differentiation of Sylvester, Lyapunov, and algebraic Riccati equations.

Ta-Chu Kao, Guillaume Hennequin

CoRR, 2020

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

Virginia Rutten, Alberto Bernacchia, Maneesh Sahani, Guillaume Hennequin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

Kristopher T. Jensen, Ta-Chu Kao, Marco Tripodi, Guillaume Hennequin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Efficient Communication over Complex Dynamical Networks.

Giacomo Baggio, Virginia Rutten, Guillaume Hennequin, Sandro Zampieri

CoRR, 2019

2018

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

Alberto Bernacchia, Máté Lengyel, Guillaume Hennequin

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Information Transmission in Dynamical Networks: The Normal Network Case.

Giacomo Baggio, Virginia Rutten, Guillaume Hennequin, Sandro Zampieri

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2014

Fast Sampling-Based Inference in Balanced Neuronal Networks.

Guillaume Hennequin, Laurence Aitchison, Máté Lengyel

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

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

Dylan Festa, Guillaume Hennequin, Máté Lengyel

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

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

Friedemann Zenke, Guillaume Hennequin, Wulfram Gerstner

PLoS Comput. Biol., 2013

2010

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

Guillaume Hennequin, Wulfram Gerstner, Jean-Pascal Pfister

Frontiers Comput. Neurosci., 2010

2009

Code-specific policy gradient rules for spiking neurons.

Henning Sprekeler, Guillaume Hennequin, Wulfram Gerstner

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