Dendritic cortical microcircuits approximate the backpropagation algorithm

26 October 2018

Papers citing "Dendritic cortical microcircuits approximate the backpropagation algorithm"

50 / 124 papers shown

Title
Minimizing Control for Credit Assignment with Strong Feedback Alexander Meulemans Matilde Tristany Farinha Maria R. Cervera João Sacramento Benjamin Grewe 22 17 0 14 Apr 2022
Deep Learning in Spiking Phasor Neural Networks Connor Bybee E. P. Frady Friedrich T. Sommer 21 6 0 01 Apr 2022
Learning by non-interfering feedback chemical signaling in physical networks Vidyesh Rao Anisetti B. Scellier J. M. Schwarz 19 17 0 22 Mar 2022
Constrained Parameter Inference as a Principle for Learning Nasir Ahmad Ellen Schrader Marcel van Gerven 20 10 0 22 Mar 2022
Deep Layer-wise Networks Have Closed-Form Weights Chieh-Tsai Wu A. Masoomi Arthur Gretton Jennifer Dy 31 3 0 01 Feb 2022
Towards Scaling Difference Target Propagation by Learning Backprop Targets M. Ernoult Fabrice Normandin A. Moudgil Sean Spinney Eugene Belilovsky Irina Rish Blake A. Richards Yoshua Bengio 19 28 0 31 Jan 2022
Learning on Arbitrary Graph Topologies via Predictive Coding Tommaso Salvatori Luca Pinchetti Beren Millidge Yuhang Song Tianyi Bao Rafal Bogacz Thomas Lukasiewicz 40 33 0 31 Jan 2022
DELAUNAY: a dataset of abstract art for psychophysical and machine learning research C. Gontier Jakob Jordan Mihai A. Petrovici 38 2 0 28 Jan 2022
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass Giorgia Dellaferrera Gabriel Kreiman 31 53 0 27 Jan 2022
Including STDP to eligibility propagation in multi-layer recurrent spiking neural networks Werner van der Veen 41 1 0 05 Jan 2022
Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time Bojian Yin Federico Corradi S. Bohté 38 61 0 20 Dec 2021
A Normative and Biologically Plausible Algorithm for Independent Component Analysis Yanis Bahroun D. Chklovskii Anirvan M. Sengupta 29 10 0 17 Nov 2021
How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization Shivam Garg Santosh Vempala 33 3 0 17 Nov 2021
BioLeaF: A Bio-plausible Learning Framework for Training of Spiking Neural Networks Yukun Yang Peng Li 29 3 0 14 Nov 2021
A New Look at Spike-Timing-Dependent Plasticity Networks for Spatio-Temporal Feature Learning A. Safa I. Ocket A. Bourdoux Hichem Sahli F. Catthoor Georges G. E. Gielen 21 8 0 01 Nov 2021
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons Paul Haider B. Ellenberger Laura Kriener Jakob Jordan Walter Senn Mihai A. Petrovici 27 24 0 27 Oct 2021
Cortico-cerebellar networks as decoupling neural interfaces J. Pemberton E. Boven Richard Apps Rui Ponte Costa 35 6 0 21 Oct 2021
Assemblies of neurons learn to classify well-separated distributions M. Dabagia Christos H. Papadimitriou Santosh Vempala 24 8 0 07 Oct 2021
Variational learning of quantum ground states on spiking neuromorphic hardware Robert Klassert A. Baumbach Mihai A. Petrovici M. Gärttner 28 7 0 30 Sep 2021
Learning through structure: towards deep neuromorphic knowledge graph embeddings Victor Caceres Chian Marcel Hildebrandt Thomas Runkler Dominik Dold GNN 16 7 0 21 Sep 2021
Learning cortical representations through perturbed and adversarial dreaming Nicolas Deperrois Mihai A. Petrovici Walter Senn Jakob Jordan GAN CLL 58 21 0 09 Sep 2021
Online Training of Spiking Recurrent Neural Networks with Phase-Change Memory Synapses Yiğit Demirağ Charlotte Frenkel Melika Payvand Giacomo Indiveri 30 17 0 04 Aug 2021
Credit Assignment in Neural Networks through Deep Feedback Control Alexander Meulemans Matilde Tristany Farinha Javier García Ordónez Pau Vilimelis Aceituno João Sacramento Benjamin Grewe 31 35 0 15 Jun 2021
The Backpropagation Algorithm Implemented on Spiking Neuromorphic Hardware Alpha Renner F. Sheldon Anatoly Zlotnik L. Tao A. Sornborger 21 38 0 13 Jun 2021
Front Contribution instead of Back Propagation Swaroop Mishra Anjana Arunkumar 17 0 0 10 Jun 2021
Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence Charlotte Frenkel D. Bol Giacomo Indiveri 36 34 0 02 Jun 2021
Neko: a Library for Exploring Neuromorphic Learning Rules Zixuan Zhao Nathan Wycoff N. Getty Rick L. Stevens Fangfang Xia 17 2 0 01 May 2021
An error-propagation spiking neural network compatible with neuromorphic processors M. Cartiglia G. Haessig Giacomo Indiveri 17 5 0 12 Apr 2021
A contrastive rule for meta-learning Nicolas Zucchet Simon Schug J. Oswald Dominic Zhao João Sacramento MLT 33 19 0 04 Apr 2021
Self-learning Machines based on Hamiltonian Echo Backpropagation V. López-Pastor F. Marquardt 54 33 0 08 Mar 2021
Reverse Differentiation via Predictive Coding Tommaso Salvatori Yuhang Song Thomas Lukasiewicz Rafal Bogacz Zhenghua Xu PINN 30 26 0 08 Mar 2021
The Yin-Yang dataset Laura Kriener Julian Goltz Mihai A. Petrovici 3DH 35 19 0 16 Feb 2021
The Neural Coding Framework for Learning Generative Models Alexander Ororbia Daniel Kifer GAN 26 65 0 07 Dec 2020
A biologically plausible neural network for local supervision in cortical microcircuits Siavash Golkar David Lipshutz Yanis Bahroun Anirvan M. Sengupta D. Chklovskii 13 7 0 30 Nov 2020
Kernel Dependence Network Chieh-Tsai Wu A. Masoomi Arthur Gretton Jennifer Dy 16 0 0 04 Nov 2020
A simple normative network approximates local non-Hebbian learning in the cortex Siavash Golkar David Lipshutz Yanis Bahroun Anirvan M. Sengupta D. Chklovskii OffRL 9 15 0 23 Oct 2020
Brain-Inspired Learning on Neuromorphic Substrates Friedemann Zenke Emre Neftci 38 89 0 22 Oct 2020
Local plasticity rules can learn deep representations using self-supervised contrastive predictions Bernd Illing Jean-Paul Ventura G. Bellec W. Gerstner SSL DRL 59 69 0 16 Oct 2020
EqSpike: Spike-driven Equilibrium Propagation for Neuromorphic Implementations Erwann Martin M. Ernoult Jérémie Laydevant Shuai-shuai Li D. Querlioz Teodora Petrisor Julie Grollier 17 49 0 15 Oct 2020
Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley 22 0 0 13 Oct 2020
Relaxing the Constraints on Predictive Coding Models Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley 26 23 0 02 Oct 2020
A biologically plausible neural network for multi-channel Canonical Correlation Analysis David Lipshutz Yanis Bahroun Siavash Golkar Anirvan M. Sengupta Dmitri B. Chkovskii 6 23 0 01 Oct 2020
Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley ODL 28 16 0 11 Sep 2020
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications M. R. Azghadi Corey Lammie Jason K. Eshraghian Melika Payvand Elisa Donati B. Linares-Barranco Giacomo Indiveri 30 139 0 11 Jul 2020
Biological credit assignment through dynamic inversion of feedforward networks William F. Podlaski C. Machens 27 19 0 10 Jul 2020
Deep Reinforcement Learning and its Neuroscientific Implications M. Botvinick Jane X. Wang Will Dabney Kevin J. Miller Z. Kurth-Nelson OffRL AI4CE 28 169 0 07 Jul 2020
Meta-Learning through Hebbian Plasticity in Random Networks Elias Najarro S. Risi 30 77 0 06 Jul 2020
A Theoretical Framework for Target Propagation Alexander Meulemans Francesco S. Carzaniga Johan A. K. Suykens João Sacramento Benjamin Grewe AAML 33 77 0 25 Jun 2020
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks Roman Pogodin P. Latham 24 34 0 12 Jun 2020
Predictive Coding Approximates Backprop along Arbitrary Computation Graphs Beren Millidge Alexander Tschantz Christopher L. Buckley 32 118 0 07 Jun 2020