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How Auto-Encoders Could Provide Credit Assignment in Deep Networks via
  Target Propagation

How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation

29 July 2014
Yoshua Bengio
ArXivPDFHTML

Papers citing "How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation"

50 / 100 papers shown
Title
Multiplicative Learning
Han Kim
Hyungjoon Soh
V. Periwal
Junghyo Jo
55
0
0
13 Mar 2025
Benchmarking Predictive Coding Networks -- Made Simple
Benchmarking Predictive Coding Networks -- Made Simple
Luca Pinchetti
Chang Qi
Oleh Lokshyn
Gaspard Olivers
Cornelius Emde
...
Simon Frieder
Bayar I. Menzat
Rafal Bogacz
Thomas Lukasiewicz
Tommaso Salvatori
132
5
0
17 Feb 2025
Sign-Symmetry Learning Rules are Robust Fine-Tuners
Sign-Symmetry Learning Rules are Robust Fine-Tuners
Aymene Berriche
Mehdi Zakaria Adjal
Riyadh Baghdadi
AAML
55
0
0
09 Feb 2025
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
Satoki Ishikawa
Rio Yokota
Ryo Karakida
49
0
0
04 Nov 2024
Ornstein-Uhlenbeck Adaptation as a Mechanism for Learning in Brains and
  Machines
Ornstein-Uhlenbeck Adaptation as a Mechanism for Learning in Brains and Machines
Jesus Garcia Fernandez
Nasir Ahmad
Marcel van Gerven
29
1
0
17 Oct 2024
Tight Stability, Convergence, and Robustness Bounds for Predictive
  Coding Networks
Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks
A. Mali
Tommaso Salvatori
Alexander Ororbia
40
0
0
07 Oct 2024
Counter-Current Learning: A Biologically Plausible Dual Network Approach
  for Deep Learning
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
Chia-Hsiang Kao
Bharath Hariharan
56
1
0
30 Sep 2024
Momentum Auxiliary Network for Supervised Local Learning
Momentum Auxiliary Network for Supervised Local Learning
Junhao Su
Changpeng Cai
Feiyu Zhu
Chenghao He
Xiaojie Xu
Dongzhi Guan
Chenyang Si
46
4
0
08 Jul 2024
Towards Biologically Plausible Computing: A Comprehensive Comparison
Towards Biologically Plausible Computing: A Comprehensive Comparison
Changze Lv
Yufei Gu
Zhengkang Guo
Zhibo Xu
Yixin Wu
...
Tianlong Li
Jianhao Zhu
Cenyuan Zhang
Zixuan Ling
Xiaoqing Zheng
38
1
0
23 Jun 2024
Contribute to balance, wire in accordance: Emergence of backpropagation from a simple, bio-plausible neuroplasticity rule
Contribute to balance, wire in accordance: Emergence of backpropagation from a simple, bio-plausible neuroplasticity rule
Xinhao Fan
S. P. Mysore
39
0
0
23 May 2024
Gradient-Free Training of Recurrent Neural Networks using Random
  Perturbations
Gradient-Free Training of Recurrent Neural Networks using Random Perturbations
Jesus Garcia Fernandez
Sander Keemink
Marcel van Gerven
AAML
47
4
0
14 May 2024
Learning Sequence Attractors in Recurrent Networks with Hidden Neurons
Learning Sequence Attractors in Recurrent Networks with Hidden Neurons
Yao Lu
Si Wu
48
3
0
03 Apr 2024
Forward Learning of Graph Neural Networks
Forward Learning of Graph Neural Networks
Namyong Park
Xing Wang
Antoine Simoulin
Shuai Yang
Grey Yang
Ryan Rossi
Puja Trivedi
Nesreen K. Ahmed
GNN
47
1
0
16 Mar 2024
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Chenxiang Ma
Jibin Wu
Chenyang Si
Kay Chen Tan
49
2
0
27 Feb 2024
A Review of Neuroscience-Inspired Machine Learning
A Review of Neuroscience-Inspired Machine Learning
Alexander Ororbia
A. Mali
Adam Kohan
Beren Millidge
Tommaso Salvatori
37
7
0
16 Feb 2024
End-to-End Training Induces Information Bottleneck through Layer-Role
  Differentiation: A Comparative Analysis with Layer-wise Training
End-to-End Training Induces Information Bottleneck through Layer-Role Differentiation: A Comparative Analysis with Layer-wise Training
Keitaro Sakamoto
Issei Sato
24
4
0
14 Feb 2024
Zenkai -- Framework For Exploring Beyond Backpropagation
Zenkai -- Framework For Exploring Beyond Backpropagation
Greg Short
28
0
0
16 Nov 2023
Brain-like Flexible Visual Inference by Harnessing Feedback-Feedforward
  Alignment
Brain-like Flexible Visual Inference by Harnessing Feedback-Feedforward Alignment
Tahereh Toosi
Elias B. Issa
21
2
0
31 Oct 2023
Improving equilibrium propagation without weight symmetry through
  Jacobian homeostasis
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
Axel Laborieux
Friedemann Zenke
30
7
0
05 Sep 2023
Biologically-Motivated Learning Model for Instructed Visual Processing
Biologically-Motivated Learning Model for Instructed Visual Processing
R. Abel
S. Ullman
27
0
0
04 Jun 2023
Implicit Regularization in Feedback Alignment Learning Mechanisms for
  Neural Networks
Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks
Zachary Robertson
Oluwasanmi Koyejo
43
0
0
02 Jun 2023
Learning efficient backprojections across cortical hierarchies in real
  time
Learning efficient backprojections across cortical hierarchies in real time
Kevin Max
Laura Kriener
Garibaldi Pineda García
Thomas Nowotny
Ismael Jaras
Walter Senn
Mihai A. Petrovici
OOD
26
15
0
20 Dec 2022
Fixed-Weight Difference Target Propagation
Fixed-Weight Difference Target Propagation
Tatsukichi Shibuya
Nakamasa Inoue
Rei Kawakami
Ikuro Sato
AAML
24
3
0
19 Dec 2022
Deep Incubation: Training Large Models by Divide-and-Conquering
Deep Incubation: Training Large Models by Divide-and-Conquering
Zanlin Ni
Yulin Wang
Jiangwei Yu
Haojun Jiang
Yu Cao
Gao Huang
VLM
20
11
0
08 Dec 2022
Predictive Coding beyond Gaussian Distributions
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
Scaling Forward Gradient With Local Losses
Scaling Forward Gradient With Local Losses
Mengye Ren
Simon Kornblith
Renjie Liao
Geoffrey E. Hinton
81
49
0
07 Oct 2022
Holomorphic Equilibrium Propagation Computes Exact Gradients Through
  Finite Size Oscillations
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations
Axel Laborieux
Friedemann Zenke
41
33
0
01 Sep 2022
A Theoretical Framework for Inference Learning
A Theoretical Framework for Inference Learning
Nick Alonso
Beren Millidge
J. Krichmar
Emre Neftci
19
16
0
01 Jun 2022
Biologically-inspired neuronal adaptation improves learning in neural
  networks
Biologically-inspired neuronal adaptation improves learning in neural networks
Yoshimasa Kubo
Eric Chalmers
Artur Luczak
25
6
0
08 Apr 2022
Signal Propagation: A Framework for Learning and Inference In a Forward
  Pass
Signal Propagation: A Framework for Learning and Inference In a Forward Pass
Adam A. Kohan
E. Rietman
H. Siegelmann
27
26
0
04 Apr 2022
Constrained Parameter Inference as a Principle for Learning
Constrained Parameter Inference as a Principle for Learning
Nasir Ahmad
Ellen Schrader
Marcel van Gerven
20
10
0
22 Mar 2022
Recent Advances and New Frontiers in Spiking Neural Networks
Recent Advances and New Frontiers in Spiking Neural Networks
Duzhen Zhang
Shuncheng Jia
Qingyu Wang
AAML
AI4CE
21
23
0
12 Mar 2022
Gradients without Backpropagation
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
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
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization
Frederik Benzing
ODL
45
23
0
28 Jan 2022
Target Propagation via Regularized Inversion
Target Propagation via Regularized Inversion
Vincent Roulet
Zaïd Harchaoui
BDL
AAML
27
4
0
02 Dec 2021
How and When Random Feedback Works: A Case Study of Low-Rank Matrix
  Factorization
How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization
Shivam Garg
Santosh Vempala
33
3
0
17 Nov 2021
On Training Implicit Models
On Training Implicit Models
Zhengyang Geng
Xinyu Zhang
Shaojie Bai
Yisen Wang
Zhouchen Lin
72
69
0
09 Nov 2021
Cascaded Compressed Sensing Networks: A Reversible Architecture for
  Layerwise Learning
Cascaded Compressed Sensing Networks: A Reversible Architecture for Layerwise Learning
Weizhi Lu
Mingrui Chen
Kai Guo
Weiyu Li
21
0
0
20 Oct 2021
Training Spiking Neural Networks Using Lessons From Deep Learning
Training Spiking Neural Networks Using Lessons From Deep Learning
Jason K. Eshraghian
Max Ward
Emre Neftci
Xinxin Wang
Gregor Lenz
Girish Dwivedi
Bennamoun
Doo Seok Jeong
Wei D. Lu
42
437
0
27 Sep 2021
Benchmarking the Accuracy and Robustness of Feedback Alignment
  Algorithms
Benchmarking the Accuracy and Robustness of Feedback Alignment Algorithms
Albert Jiménez Sanfiz
Mohamed Akrout
OOD
AAML
22
8
0
30 Aug 2021
Feature Alignment as a Generative Process
Feature Alignment as a Generative Process
T. S. Farias
Jonas Maziero
DiffM
BDL
28
1
0
23 Jun 2021
Credit Assignment in Neural Networks through Deep Feedback Control
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
Credit Assignment Through Broadcasting a Global Error Vector
Credit Assignment Through Broadcasting a Global Error Vector
David G. Clark
L. F. Abbott
SueYeon Chung
30
23
0
08 Jun 2021
Bilevel Programs Meet Deep Learning: A Unifying View on Inference
  Learning Methods
Bilevel Programs Meet Deep Learning: A Unifying View on Inference Learning Methods
Christopher Zach
FedML
16
5
0
15 May 2021
Meta-Learning Bidirectional Update Rules
Meta-Learning Bidirectional Update Rules
Mark Sandler
Max Vladymyrov
A. Zhmoginov
Nolan Miller
Andrew Jackson
T. Madams
Blaise Agüera y Arcas
27
15
0
10 Apr 2021
Reverse Differentiation via Predictive Coding
Reverse Differentiation via Predictive Coding
Tommaso Salvatori
Yuhang Song
Thomas Lukasiewicz
Rafal Bogacz
Zhenghua Xu
PINN
30
26
0
08 Mar 2021
Gradient-adjusted Incremental Target Propagation Provides Effective
  Credit Assignment in Deep Neural Networks
Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks
Sander Dalm
Nasir Ahmad
L. Ambrogioni
Marcel van Gerven
36
1
0
23 Feb 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey
  on the Provably Optimal Methods
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
Differentiable Programming à la Moreau
Vincent Roulet
Zaïd Harchaoui
23
5
0
31 Dec 2020
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