Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2006.14331
Cited By
v1
v2
v3
v4 (latest)
A Theoretical Framework for Target Propagation
25 June 2020
Alexander Meulemans
Francesco S. Carzaniga
Johan A. K. Suykens
João Sacramento
Benjamin Grewe
AAML
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"A Theoretical Framework for Target Propagation"
48 / 48 papers shown
Information-Theoretic Greedy Layer-wise Training for Traffic Sign Recognition
Shuyan Lyu
Zhanzimo Wu
Junliang Du
124
0
0
31 Oct 2025
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
International Conference on Learning Representations (ICLR), 2024
Satoki Ishikawa
Rio Yokota
Ryo Karakida
456
1
0
04 Nov 2024
Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks
A. Mali
Tommaso Salvatori
Alexander Ororbia
270
5
0
07 Oct 2024
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
Neural Information Processing Systems (NeurIPS), 2024
Chia-Hsiang Kao
Bharath Hariharan
337
3
0
30 Sep 2024
Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks
Tianyu Zheng
Liyuan Han
Tielin Zhang
AI4CE
273
3
0
26 Aug 2024
Contribute to balance, wire in accordance: Emergence of backpropagation from a simple, bio-plausible neuroplasticity rule
bioRxiv (bioRxiv), 2024
Xinhao Fan
S. P. Mysore
296
1
0
23 May 2024
Forward Learning of Graph Neural Networks
Namyong Park
Xing Wang
Antoine Simoulin
Shuai Yang
Grey Yang
Ryan Rossi
Puja Trivedi
Nesreen K. Ahmed
GNN
363
1
0
16 Mar 2024
A Review of Neuroscience-Inspired Machine Learning
Alexander Ororbia
A. Mali
Adam Kohan
Beren Millidge
Tommaso Salvatori
329
16
0
16 Feb 2024
Go beyond End-to-End Training: Boosting Greedy Local Learning with Context Supply
IEEE Transactions on Artificial Intelligence (IEEE TAI), 2023
Chengting Yu
Fengzhao Zhang
Hanzhi Ma
Aili Wang
Er-ping Li
238
1
0
12 Dec 2023
Zenkai -- Framework For Exploring Beyond Backpropagation
Greg Short
218
0
0
16 Nov 2023
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
International Conference on Learning Representations (ICLR), 2023
Axel Laborieux
Friedemann Zenke
428
10
0
05 Sep 2023
Biologically-Motivated Learning Model for Instructed Visual Processing
R. Abel
S. Ullman
361
0
0
04 Jun 2023
Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks
International Conference on Machine Learning (ICML), 2023
Zachary Robertson
Oluwasanmi Koyejo
400
0
0
02 Jun 2023
Understanding Predictive Coding as an Adaptive Trust-Region Method
Francesco Innocenti
Ryan Singh
Christopher L. Buckley
360
1
0
29 May 2023
Block-local learning with probabilistic latent representations
David Kappel
Khaleelulla Khan Nazeer
Cabrel Teguemne Fokam
Christian Mayr
Anand Subramoney
300
5
0
24 May 2023
Lazy learning: a biologically-inspired plasticity rule for fast and energy efficient synaptic plasticity
Aaron Pache
M. V. Rossum
263
2
0
26 Mar 2023
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons
International Conference on Machine Learning (ICML), 2023
R. Høier
D. Staudt
Christopher Zach
497
14
0
02 Feb 2023
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
326
21
0
20 Dec 2022
Fixed-Weight Difference Target Propagation
AAAI Conference on Artificial Intelligence (AAAI), 2022
Tatsukichi Shibuya
Nakamasa Inoue
Rei Kawakami
Ikuro Sato
AAML
166
6
0
19 Dec 2022
Is Bio-Inspired Learning Better than Backprop? Benchmarking Bio Learning vs. Backprop
Manas Gupta
Sarthak Ketanbhai Modi
Hang Zhang
Joon Hei Lee
J. Lim
346
8
0
09 Dec 2022
Predictive Coding beyond Gaussian Distributions
Neural Information Processing Systems (NeurIPS), 2022
Luca Pinchetti
Tommaso Salvatori
Yordan Yordanov
Beren Millidge
Yuhang Song
Thomas Lukasiewicz
UQCV
BDL
269
20
0
07 Nov 2022
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations
Neural Information Processing Systems (NeurIPS), 2022
Axel Laborieux
Friedemann Zenke
361
51
0
01 Sep 2022
ATLAS: Universal Function Approximator for Memory Retention
H. V. Deventer
Anna Sergeevna Bosman
152
0
0
10 Aug 2022
A Theoretical Framework for Inference and Learning in Predictive Coding Networks
International Conference on Learning Representations (ICLR), 2022
Beren Millidge
Yuhang Song
Tommaso Salvatori
Thomas Lukasiewicz
Rafal Bogacz
314
22
0
21 Jul 2022
The least-control principle for local learning at equilibrium
Neural Information Processing Systems (NeurIPS), 2022
Alexander Meulemans
Nicolas Zucchet
Seijin Kobayashi
J. Oswald
João Sacramento
254
32
0
04 Jul 2022
A Theoretical Framework for Inference Learning
Neural Information Processing Systems (NeurIPS), 2022
Nick Alonso
Beren Millidge
J. Krichmar
Emre Neftci
331
23
0
01 Jun 2022
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning
International Conference on Learning Representations (ICLR), 2022
Beren Millidge
Yuhang Song
Tommaso Salvatori
Thomas Lukasiewicz
Rafal Bogacz
448
30
0
31 May 2022
Minimizing Control for Credit Assignment with Strong Feedback
International Conference on Machine Learning (ICML), 2022
Alexander Meulemans
Matilde Tristany Farinha
Maria R. Cervera
João Sacramento
Benjamin Grewe
294
24
0
14 Apr 2022
Gradients without Backpropagation
A. G. Baydin
Barak A. Pearlmutter
Don Syme
Frank Wood
Juil Sock
220
89
0
17 Feb 2022
Towards Scaling Difference Target Propagation by Learning Backprop Targets
International Conference on Machine Learning (ICML), 2022
M. Ernoult
Fabrice Normandin
A. Moudgil
Sean Spinney
Eugene Belilovsky
Irina Rish
Blake A. Richards
Yoshua Bengio
271
45
0
31 Jan 2022
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization
International Conference on Machine Learning (ICML), 2022
Frederik Benzing
ODL
349
31
0
28 Jan 2022
Target Propagation via Regularized Inversion
Vincent Roulet
Zaïd Harchaoui
BDL
AAML
292
5
0
02 Dec 2021
On Training Implicit Models
Neural Information Processing Systems (NeurIPS), 2021
Zhengyang Geng
Xinyu Zhang
Shaojie Bai
Yisen Wang
Zhouchen Lin
420
95
0
09 Nov 2021
Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks
Mufeng Tang
Jianlong Wu
Y. Amit
SSL
439
11
0
30 Sep 2021
KCNet: An Insect-Inspired Single-Hidden-Layer Neural Network with Randomized Binary Weights for Prediction and Classification Tasks
Jinyung Hong
Theodore P. Pavlic
MQ
210
4
0
17 Aug 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience
Beren Millidge
DRL
399
11
0
30 Jun 2021
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective
Akhilan Boopathy
Ila Fiete
245
14
0
15 Jun 2021
Credit Assignment in Neural Networks through Deep Feedback Control
Neural Information Processing Systems (NeurIPS), 2021
Alexander Meulemans
Matilde Tristany Farinha
Javier García Ordónez
Pau Vilimelis Aceituno
João Sacramento
Benjamin Grewe
382
46
0
15 Jun 2021
Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence
Proceedings of the IEEE (Proc. IEEE), 2021
Charlotte Frenkel
D. Bol
Giacomo Indiveri
299
60
0
02 Jun 2021
Bilevel Programs Meet Deep Learning: A Unifying View on Inference Learning Methods
Christopher Zach
FedML
212
6
0
15 May 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods
IEEE Computational Intelligence Magazine (IEEE CIM), 2021
Shiyu Duan
José C. Príncipe
MQ
475
8
0
09 Jan 2021
Differentiable Programming à la Moreau
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
Vincent Roulet
Zaïd Harchaoui
309
5
0
31 Dec 2020
Self Normalizing Flows
International Conference on Machine Learning (ICML), 2020
Thomas Anderson Keller
Jorn W. T. Peters
P. Jaini
Emiel Hoogeboom
Patrick Forré
Max Welling
320
14
0
14 Nov 2020
Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm
Beren Millidge
Alexander Tschantz
A. Seth
Christopher L. Buckley
176
1
0
13 Oct 2020
Feed-Forward On-Edge Fine-tuning Using Static Synthetic Gradient Modules
R. Neven
Marian Verhelst
Tinne Tuytelaars
Toon Goedemé
207
1
0
21 Sep 2020
Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain
Beren Millidge
Alexander Tschantz
A. Seth
Christopher L. Buckley
ODL
366
19
0
11 Sep 2020
Neural Networks with Recurrent Generative Feedback
Neural Information Processing Systems (NeurIPS), 2020
Yujia Huang
James Gornet
Sihui Dai
Zhiding Yu
T. Nguyen
Doris Y. Tsao
Anima Anandkumar
AAML
GAN
258
45
0
17 Jul 2020
Biological credit assignment through dynamic inversion of feedforward networks
Neural Information Processing Systems (NeurIPS), 2020
William F. Podlaski
C. Machens
254
22
0
10 Jul 2020
1
Page 1 of 1
