Biologically plausible deep learning -- but how far can we go with shallow networks?

27 February 2019

Papers citing "Biologically plausible deep learning -- but how far can we go with shallow networks?"

19 / 19 papers shown

Title
From Neurons to Computation: Biological Reservoir Computing for Pattern Recognition Ludovico Iannello Luca Ciampi Gabriele Lagani Fabrizio Tonelli Eleonora Crocco Lucio Maria Calcagnile Angelo Di Garbo F. Cremisi Giuseppe Amato 49 0 0 06 May 2025
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey Gabriele Lagani Fabrizio Falchi Claudio Gennaro Giuseppe Amato AAML 43 6 0 30 Jul 2023
Synaptic Dynamics Realize First-order Adaptive Learning and Weight Symmetry Yukun Yang Peng Li ODL 38 1 0 01 Dec 2022
Multi-level Data Representation For Training Deep Helmholtz Machines J. M. Ramos Luis Sa-Couto Andreas Wichert 18 0 0 26 Oct 2022
Brain-like combination of feedforward and recurrent network components achieves prototype extraction and robust pattern recognition Naresh B. Ravichandran A. Lansner Pawel Herman 32 4 0 30 Jun 2022
BioLeaF: A Bio-plausible Learning Framework for Training of Spiking Neural Networks Yukun Yang Peng Li 27 3 0 14 Nov 2021
Training Deep Spiking Auto-encoders without Bursting or Dying Neurons through Regularization Justus F. Hübotter Pablo Lanillos Jakub M. Tomczak 16 3 0 22 Sep 2021
BioLCNet: Reward-modulated Locally Connected Spiking Neural Networks Hafez Ghaemi Erfan Mirzaei Mahbod Nouri Saeed Reza Kheradpisheh 16 2 0 12 Sep 2021
SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft Winner-Take-All Networks Timoleon Moraitis Dmitry Toichkin Adrien Journé Yansong Chua Qinghai Guo AAML BDL 68 28 0 12 Jul 2021
Using brain inspired principles to unsupervisedly learn good representations for visual pattern recognition Luis Sa-Couto Andreas Wichert SSL OOD 14 9 0 30 Apr 2021
Reverse Differentiation via Predictive Coding Tommaso Salvatori Yuhang Song Thomas Lukasiewicz Rafal Bogacz Zhenghua Xu PINN 30 26 0 08 Mar 2021
Predictive Coding Can Do Exact Backpropagation on Convolutional and Recurrent Neural Networks Tommaso Salvatori Yuhang Song Thomas Lukasiewicz Rafal Bogacz Zhenghua Xu PINN 27 24 0 05 Mar 2021
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks Roman Pogodin P. Latham 24 34 0 12 Jun 2020
Brain-like approaches to unsupervised learning of hidden representations -- a comparative study Naresh B. Ravichandran A. Lansner Pawel Herman BDL SSL 14 12 0 06 May 2020
Binary autoencoder with random binary weights V. Osaulenko MQ 18 3 0 30 Apr 2020
Learning representations in Bayesian Confidence Propagation neural networks Naresh B. Ravichandran A. Lansner Pawel Herman BDL SSL 12 14 0 27 Mar 2020
Fast and energy-efficient neuromorphic deep learning with first-spike times Julian Goltz Laura Kriener A. Baumbach Sebastian Billaudelle O. Breitwieser ... Á. F. Kungl Walter Senn Johannes Schemmel K. Meier Mihai A. Petrovici 35 126 0 24 Dec 2019
Long short-term memory and learning-to-learn in networks of spiking neurons G. Bellec Darjan Salaj Anand Subramoney Robert Legenstein Wolfgang Maass 121 481 0 26 Mar 2018
Neuromorphic Deep Learning Machines Emre Neftci C. Augustine Somnath Paul Georgios Detorakis BDL 135 258 0 16 Dec 2016