How Important is Weight Symmetry in Backpropagation?

17 October 2015

Papers citing "How Important is Weight Symmetry in Backpropagation?"

41 / 91 papers shown

Title
MAP Propagation Algorithm: Faster Learning with a Team of Reinforcement Learning Agents Stephen Chung 6 5 0 15 Oct 2020
Differentially Private Deep Learning with Direct Feedback Alignment Jaewoo Lee Daniel Kifer FedML 9 9 0 08 Oct 2020
Relaxing the Constraints on Predictive Coding Models Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley 23 23 0 02 Oct 2020
Deriving Differential Target Propagation from Iterating Approximate Inverses Yoshua Bengio 10 24 0 29 Jul 2020
A Theoretical Framework for Target Propagation Alexander Meulemans Francesco S. Carzaniga Johan A. K. Suykens João Sacramento Benjamin Grewe AAML 27 77 0 25 Jun 2020
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures Julien Launay Iacopo Poli Franccois Boniface Florent Krzakala 36 62 0 23 Jun 2020
Learning to Learn with Feedback and Local Plasticity Jack W Lindsey Ashok Litwin-Kumar CLL 34 32 0 16 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 30 118 0 07 Jun 2020
Two Routes to Scalable Credit Assignment without Weight Symmetry D. Kunin Aran Nayebi Javier Sagastuy-Breña Surya Ganguli Jonathan M. Bloom Daniel L. K. Yamins 31 31 0 28 Feb 2020
A Deep Unsupervised Feature Learning Spiking Neural Network with Binarized Classification Layers for EMNIST Classification using SpykeFlow Ruthvik Vaila John N. Chiasson V. Saxena 19 22 0 26 Feb 2020
Large-Scale Gradient-Free Deep Learning with Recursive Local Representation Alignment Alexander Ororbia A. Mali Daniel Kifer C. Lee Giles 13 2 0 10 Feb 2020
Questions to Guide the Future of Artificial Intelligence Research J. Ott 14 3 0 21 Dec 2019
Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks Charlotte Frenkel M. Lefebvre D. Bol 11 23 0 03 Sep 2019
Temporal Coding in Spiking Neural Networks with Alpha Synaptic Function: Learning with Backpropagation Iulia Comsa Krzysztof Potempa Luca Versari T. Fischbacher Andrea Gesmundo J. Alakuijala 23 174 0 30 Jul 2019
Deep Active Inference as Variational Policy Gradients Beren Millidge BDL 32 103 0 08 Jul 2019
Principled Training of Neural Networks with Direct Feedback Alignment Julien Launay Iacopo Poli Florent Krzakala 19 35 0 11 Jun 2019
Learning to solve the credit assignment problem B. Lansdell P. Prakash Konrad Paul Kording 11 50 0 03 Jun 2019
Deep Convolutional Spiking Neural Networks for Image Classification Ruthvik Vaila John N. Chiasson V. Saxena 10 31 0 28 Mar 2019
Efficient Convolutional Neural Network Training with Direct Feedback Alignment Donghyeon Han H. Yoo 3DV 16 17 0 06 Jan 2019
Feedback alignment in deep convolutional networks Theodore H. Moskovitz Ashok Litwin-Kumar L. F. Abbott 27 59 0 12 Dec 2018
Deep learning with asymmetric connections and Hebbian updates Y. Amit 13 43 0 19 Nov 2018
Biologically-plausible learning algorithms can scale to large datasets Y. Chitour Honglin Chen Zhenyu Liao T. Poggio 11 73 0 08 Nov 2018
Error Forward-Propagation: Reusing Feedforward Connections to Propagate Errors in Deep Learning Adam A. Kohan E. Rietman H. Siegelmann 55 24 0 09 Aug 2018
Backprop Evolution Maximilian Alber Irwan Bello Barret Zoph Pieter-Jan Kindermans Prajit Ramachandran Quoc V. Le 8 9 0 08 Aug 2018
Biologically Motivated Algorithms for Propagating Local Target Representations Alexander Ororbia A. Mali 20 87 0 26 May 2018
Dictionary Learning by Dynamical Neural Networks Tsung-Han Lin P. T. P. Tang PINN AI4CE 9 10 0 23 May 2018
Conducting Credit Assignment by Aligning Local Representations Alexander Ororbia A. Mali Daniel Kifer C. Lee Giles ODL 23 29 0 05 Mar 2018
Learning to Adapt by Minimizing Discrepancy Alexander Ororbia P. Haffner David Reitter C. Lee Giles AI4TS 21 28 0 30 Nov 2017
Variational Probability Flow for Biologically Plausible Training of Deep Neural Networks Zuozhu Liu Tony Q.S. Quek Shaowei Lin 14 3 0 21 Nov 2017
Deep supervised learning using local errors Hesham Mostafa V. Ramesh Gert Cauwenberghs 25 113 0 17 Nov 2017
Building machines that adapt and compute like brains Brenden M. Lake J. Tenenbaum AI4CE FedML NAI AILaw 254 890 0 11 Nov 2017
Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning Georgios Detorakis Sadique Sheik C. Augustine Somnath Paul Bruno U. Pedroni N. Dutt J. Krichmar Gert Cauwenberghs Emre Neftci 33 29 0 29 Sep 2017
CATERPILLAR: Coarse Grain Reconfigurable Architecture for Accelerating the Training of Deep Neural Networks Yuanfang Li A. Pedram 9 19 0 01 Jun 2017
Neuromorphic Deep Learning Machines Emre Neftci C. Augustine Somnath Paul Georgios Detorakis BDL 135 258 0 16 Dec 2016
Learning in the Machine: Random Backpropagation and the Deep Learning Channel Pierre Baldi Peter Sadowski Zhiqin Lu AAML 18 16 0 08 Dec 2016
Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning Q. Liao Kenji Kawaguchi T. Poggio 24 28 0 19 Oct 2016
Direct Feedback Alignment Provides Learning in Deep Neural Networks Arild Nøkland ODL 11 447 0 06 Sep 2016
Review of state-of-the-arts in artificial intelligence with application to AI safety problem V. Shakirov 17 10 0 11 May 2016
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex Q. Liao T. Poggio 213 255 0 13 Apr 2016
MatConvNet - Convolutional Neural Networks for MATLAB Andrea Vedaldi Karel Lenc 183 2,946 0 15 Dec 2014