Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets

25 January 2019

Papers citing "Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets"

36 / 36 papers shown

Title
Three-Factor Learning in Spiking Neural Networks: An Overview of Methods and Trends from a Machine Learning Perspective Szymon Mazurek Jakub Caputa Jan K. Argasiñski Maciej Wielgosz 26 0 0 06 Apr 2025
Emulating Brain-like Rapid Learning in Neuromorphic Edge Computing Kenneth Stewart Michael Neumeier Sumit Bam Shrestha Garrick Orchard Emre Neftci 47 0 0 28 Aug 2024
Analog Spiking Neuron in CMOS 28 nm Towards Large-Scale Neuromorphic Processors M. Besrour Jacob Lavoie Takwa Omrani Gabriel Martin-Hardy Esmaeil Ranjbar Koleibi Jérémy Ménard K. Koua Philippe Marcoux Mounir Boukadoum Réjean Fontaine 39 1 0 14 Aug 2024
Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing Thomas Ortner Horst Petschenig Athan Vasilopoulos Roland Renner Spela Brglez Thomas Limbacher Enrique Pinero Alejandro Linares Barranco A. Pantazi Robert Legenstein 45 0 0 22 Apr 2024
Learning Object Permanence from Videos via Latent Imaginations Manuel Traub Frederic Becker S. Otte Martin Volker Butz 33 1 0 16 Oct 2023
A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning Heng Zhang Danilo Vasconcellos Vargas AI4CE 33 17 0 27 Jul 2023
Synaptic motor adaptation: A three-factor learning rule for adaptive robotic control in spiking neural networks Samuel Schmidgall Joe Hays 32 3 0 02 Jun 2023
Exploring the Promise and Limits of Real-Time Recurrent Learning Kazuki Irie Anand Gopalakrishnan Jürgen Schmidhuber 32 15 0 30 May 2023
Efficient LSTM Training with Eligibility Traces Mitchell L. Hoyer Shahram Eivazi S. Otte 9 1 0 30 Sep 2022
A Taxonomy of Recurrent Learning Rules Guillermo Martín-Sánchez Sander M. Bohté S. Otte 29 3 0 23 Jul 2022
Learning to learn online with neuromodulated synaptic plasticity in spiking neural networks Samuel Schmidgall Joe Hays 46 3 0 25 Jun 2022
Emergent organization of receptive fields in networks of excitatory and inhibitory neurons Leon Lufkin Ashish Puri Ganlin Song Xinyi Zhong John D. Lafferty 21 1 0 26 May 2022
Learning What and Where: Disentangling Location and Identity Tracking Without Supervision Manuel Traub S. Otte Tobias Menge Matthias Karlbauer Jannik Thummel Martin Volker Butz 34 20 0 26 May 2022
Meta-learning Spiking Neural Networks with Surrogate Gradient Descent Kenneth Stewart Emre Neftci 35 25 0 26 Jan 2022
Including STDP to eligibility propagation in multi-layer recurrent spiking neural networks Werner van der Veen 41 1 0 05 Jan 2022
Cortico-cerebellar networks as decoupling neural interfaces J. Pemberton E. Boven Richard Apps Rui Ponte Costa 35 6 0 21 Oct 2021
Convergence and Alignment of Gradient Descent with Random Backpropagation Weights Ganlin Song Ruitu Xu John D. Lafferty ODL 59 21 0 10 Jun 2021
Time Series Analysis and Modeling to Forecast: a Survey F. Dama Christine Sinoquet AI4TS 24 27 0 31 Mar 2021
A Spiking Central Pattern Generator for the control of a simulated lamprey robot running on SpiNNaker and Loihi neuromorphic boards Emmanouil Angelidis Emanuel Buchholz Jonathan Arreguit A. Rougé T. Stewart Axel Von Arnim Alois C. Knoll A. Ijspeert 38 28 0 18 Jan 2021
Hybrid Backpropagation Parallel Reservoir Networks Matthew Evanusa Snehesh Shrestha M. Girvan Cornelia Fermuller Yiannis Aloimonos AI4TS 35 0 0 27 Oct 2020
Tuning Convolutional Spiking Neural Network with Biologically-plausible Reward Propagation Tielin Zhang Shuncheng Jia Xiang Cheng Bo Xu 36 48 0 09 Oct 2020
Event-Driven Visual-Tactile Sensing and Learning for Robots Tasbolat Taunyazov Weicong Sng H. See Brian Z. H. Lim Jethro Kuan Abdul Fatir Ansari Benjamin C. K. Tee Harold Soh 28 92 0 15 Sep 2020
Universality of Gradient Descent Neural Network Training G. Welper 29 7 0 27 Jul 2020
A bio-inspired bistable recurrent cell allows for long-lasting memory Nicolas Vecoven D. Ernst G. Drion RALM 13 18 0 09 Jun 2020
Learning Precise Spike Timings with Eligibility Traces Manuel Traub Martin Volker Butz R. Baayen S. Otte 6 2 0 08 May 2020
Verification and Design Methods for the BrainScaleS Neuromorphic Hardware System Andreas Grübl Sebastian Billaudelle Benjamin Cramer V. Karasenko Johannes Schemmel 24 33 0 25 Mar 2020
Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks Wenrui Zhang Peng Li 16 215 0 24 Feb 2020
A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design Yusuke Sakemi K. Morino Takashi Morie Kazuyuki Aihara 8 32 0 08 Jan 2020
Modeling somatic computation with non-neural bioelectric networks Santosh Manicka M. Levin 12 35 0 09 Dec 2019
Deep Semantic Segmentation of Natural and Medical Images: A Review Saeid Asgari Taghanaki Kumar Abhishek Joseph Paul Cohen Julien Cohen-Adad Ghassan Hamarneh SSeg VLM 45 668 0 16 Oct 2019
Reservoirs learn to learn Anand Subramoney Franz Scherr Wolfgang Maass 11 19 0 16 Sep 2019
Reinforcement Learning with Low-Complexity Liquid State Machines Wachirawit Ponghiran G. Srinivasan Kaushik Roy 17 14 0 04 Jun 2019
Embodied Neuromorphic Vision with Event-Driven Random Backpropagation Jacques Kaiser Alexander Friedrich J. C. V. Tieck Daniel Reichard A. Rönnau Emre Neftci Rüdiger Dillmann 13 6 0 09 Apr 2019
Surrogate Gradient Learning in Spiking Neural Networks Emre Neftci Hesham Mostafa Friedemann Zenke 21 1,211 0 28 Jan 2019
Long short-term memory and learning-to-learn in networks of spiking neurons G. Bellec Darjan Salaj Anand Subramoney Robert Legenstein Wolfgang Maass 121 483 0 26 Mar 2018
Building machines that adapt and compute like brains Brenden M. Lake J. Tenenbaum AI4CE FedML NAI AILaw 254 889 0 11 Nov 2017