Exploring hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn

28 February 2022

Papers citing "Exploring hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn"

8 / 8 papers shown

Title
Convolutional Spiking Neural Network for Image Classification Mikhail Kiselev Andrey Lavrentyev 3DH 44 0 0 13 May 2025
Vast TVB parameter space exploration: A Modular Framework for Accelerating the Multi-Scale Simulation of Human Brain Dynamics Michiel A. van der Vlag L. Kusch A. Destexhe Viktor Jirsa Sandra Díaz-Pier Jennifer S. Goldman 14 1 0 22 Nov 2023
Two-compartment neuronal spiking model expressing brain-state specific apical-amplification, -isolation and -drive regimes E. Pastorelli Alper Yegenoglu Nicole Kolodziej Willem Wybo F. Simula Sandra Diaz Johan F. Storm P. Paolucci 19 3 0 10 Nov 2023
Emergent communication enhances foraging behaviour in evolved swarms controlled by Spiking Neural Networks Cristian Jimenez-Romero Alper Yegenoglu Aarón Pérez Martín Sandra Díaz-Pier A. Morrison 27 2 0 16 Dec 2022
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 193 498 0 11 Jun 2018
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 165 666 0 07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 314 11,681 0 09 Mar 2017
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 264 5,326 0 05 Nov 2016