A Theoretical Framework for Target Propagation

25 June 2020

Alexander Meulemans

Francesco S. Carzaniga

Papers citing "A Theoretical Framework for Target Propagation"

24 / 24 papers shown

Title
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation Satoki Ishikawa Rio Yokota Ryo Karakida 46 0 0 04 Nov 2024
Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks A. Mali Tommaso Salvatori Alexander Ororbia 37 0 0 07 Oct 2024
Contribute to balance, wire in accordance: Emergence of backpropagation from a simple, bio-plausible neuroplasticity rule Xinhao Fan S. P. Mysore 37 0 0 23 May 2024
Go beyond End-to-End Training: Boosting Greedy Local Learning with Context Supply Chengting Yu Fengzhao Zhang Hanzhi Ma Aili Wang Er-ping Li 29 1 0 12 Dec 2023
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis Axel Laborieux Friedemann Zenke 25 7 0 05 Sep 2023
Biologically-Motivated Learning Model for Instructed Visual Processing R. Abel S. Ullman 25 0 0 04 Jun 2023
Block-local learning with probabilistic latent representations David Kappel Khaleelulla Khan Nazeer Cabrel Teguemne Fokam Christian Mayr Anand Subramoney 24 4 0 24 May 2023
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons R. Høier D. Staudt Christopher Zach 31 11 0 02 Feb 2023
Is Bio-Inspired Learning Better than Backprop? Benchmarking Bio Learning vs. Backprop Manas Gupta Sarthak Ketanbhai Modi Hang Zhang Joon Hei Lee J. Lim 27 7 0 09 Dec 2022
Predictive Coding beyond Gaussian Distributions Luca Pinchetti Tommaso Salvatori Yordan Yordanov Beren Millidge Yuhang Song Thomas Lukasiewicz UQCV BDL 32 11 0 07 Nov 2022
ATLAS: Universal Function Approximator for Memory Retention H. V. Deventer Anna Sergeevna Bosman 27 0 0 10 Aug 2022
A Theoretical Framework for Inference and Learning in Predictive Coding Networks Beren Millidge Yuhang Song Tommaso Salvatori Thomas Lukasiewicz Rafal Bogacz 34 12 0 21 Jul 2022
Gradients without Backpropagation A. G. Baydin Barak A. Pearlmutter Don Syme Frank Wood Philip Torr 38 66 0 17 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
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization Frederik Benzing ODL 43 23 0 28 Jan 2022
Target Propagation via Regularized Inversion Vincent Roulet Zaïd Harchaoui BDL AAML 27 4 0 02 Dec 2021
On Training Implicit Models Zhengyang Geng Xinyu Zhang Shaojie Bai Yisen Wang Zhouchen Lin 72 69 0 09 Nov 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 22 7 0 30 Jun 2021
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective Akhilan Boopathy Ila Fiete 39 9 0 15 Jun 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
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods Shiyu Duan José C. Príncipe MQ 38 3 0 09 Jan 2021
Differentiable Programming à la Moreau Vincent Roulet Zaïd Harchaoui 23 5 0 31 Dec 2020
Self Normalizing Flows Thomas Anderson Keller Jorn W. T. Peters P. Jaini Emiel Hoogeboom Patrick Forré Max Welling 30 14 0 14 Nov 2020
Biological credit assignment through dynamic inversion of feedforward networks William F. Podlaski C. Machens 24 19 0 10 Jul 2020