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2407.01163
Cited By
Benchmarking Predictive Coding Networks -- Made Simple
17 February 2025
Luca Pinchetti
Chang Qi
Oleh Lokshyn
Gaspard Olivers
Cornelius Emde
Mufeng Tang
Amine MĆharrak
Simon Frieder
Bayar I. Menzat
Rafal Bogacz
Thomas Lukasiewicz
Tommaso Salvatori
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Papers citing
"Benchmarking Predictive Coding Networks -- Made Simple"
36 / 36 papers shown
Title
Bidirectional predictive coding
Gaspard Oliviers
Mufeng Tang
Rafal Bogacz
80
0
0
29 May 2025
Bayesian Predictive Coding
Alexander Tschantz
Magnus T. Koudahl
Hampus Linander
Lancelot Da Costa
Conor Heins
Jeff Beck
Christopher L. Buckley
BDL
119
0
0
31 Mar 2025
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
Satoki Ishikawa
Rio Yokota
Ryo Karakida
129
0
0
04 Nov 2024
Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks
A. Mali
Tommaso Salvatori
Alexander Ororbia
80
3
0
07 Oct 2024
Energy-based learning algorithms for analog computing: a comparative study
B. Scellier
M. Ernoult
Jack D. Kendall
Suhas Kumar
76
31
0
22 Dec 2023
Sample as You Infer: Predictive Coding With Langevin Dynamics
Umais Zahid
Qinghai Guo
Zafeirios Fountas
DRL
BDL
66
7
0
22 Nov 2023
Supervised structure learning
Karl J. Friston
Lancelot Da Costa
Alexander Tschantz
Alex B. Kiefer
Tommaso Salvatori
...
Noor Sajid
Dimitrije Marković
Thomas Parr
Tim Verbelen
Christopher L. Buckley
DRL
110
10
0
17 Nov 2023
Understanding and Improving Optimization in Predictive Coding Networks
Nick Alonso
J. Krichmar
Emre Neftci
129
7
0
23 May 2023
Sequential Memory with Temporal Predictive Coding
Mufeng Tang
Helen C. Barron
Rafal Bogacz
76
19
0
19 May 2023
The Forward-Forward Algorithm: Some Preliminary Investigations
Geoffrey E. Hinton
118
277
0
27 Dec 2022
Predictive Coding beyond Gaussian Distributions
Luca Pinchetti
Tommaso Salvatori
Yordan Yordanov
Beren Millidge
Yuhang Song
Thomas Lukasiewicz
UQCV
BDL
74
11
0
07 Nov 2022
Hebbian Deep Learning Without Feedback
Adrien Journé
Hector Garcia Rodriguez
Qinghai Guo
Timoleon Moraitis
AAML
91
54
0
23 Sep 2022
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations
Axel Laborieux
Friedemann Zenke
106
37
0
01 Sep 2022
A Theoretical Framework for Inference and Learning in Predictive Coding Networks
Beren Millidge
Yuhang Song
Tommaso Salvatori
Thomas Lukasiewicz
Rafal Bogacz
84
15
0
21 Jul 2022
A Theoretical Framework for Inference Learning
Nick Alonso
Beren Millidge
J. Krichmar
Emre Neftci
97
19
0
01 Jun 2022
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning
Beren Millidge
Yuhang Song
Tommaso Salvatori
Thomas Lukasiewicz
Rafal Bogacz
86
22
0
31 May 2022
BayesPCN: A Continually Learnable Predictive Coding Associative Memory
Jason Yoo
F. Wood
KELM
164
9
0
20 May 2022
Signal Propagation: A Framework for Learning and Inference In a Forward Pass
Adam A. Kohan
E. Rietman
H. Siegelmann
77
27
0
04 Apr 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
87
32
0
31 Jan 2022
Learning on Arbitrary Graph Topologies via Predictive Coding
Tommaso Salvatori
Luca Pinchetti
Beren Millidge
Yuhang Song
Tianyi Bao
Rafal Bogacz
Thomas Lukasiewicz
115
37
0
31 Jan 2022
Equinox: neural networks in JAX via callable PyTrees and filtered transformations
Patrick Kidger
Cristian Garcia
78
126
0
30 Oct 2021
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
309
952
0
21 Oct 2021
Associative Memories via Predictive Coding
Tommaso Salvatori
Yuhang Song
Yujian Hong
Simon Frieder
Lei Sha
Zhenghua Xu
Rafal Bogacz
Thomas Lukasiewicz
92
66
0
16 Sep 2021
SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft Winner-Take-All Networks
Timoleon Moraitis
Dmitry Toichkin
Adrien Journé
Yansong Chua
Qinghai Guo
AAML
BDL
160
29
0
12 Jul 2021
The Neural Coding Framework for Learning Generative Models
Alexander Ororbia
Daniel Kifer
GAN
101
68
0
07 Dec 2020
Energy-based Out-of-distribution Detection
Weitang Liu
Xiaoyun Wang
John Douglas Owens
Yixuan Li
OODD
377
1,382
0
08 Oct 2020
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures
Julien Launay
Iacopo Poli
Franccois Boniface
Florent Krzakala
127
64
0
23 Jun 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
Will Grathwohl
Kuan-Chieh Wang
J. Jacobsen
David Duvenaud
Mohammad Norouzi
Kevin Swersky
VLM
108
547
0
06 Dec 2019
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks
Kevin Gimpel
UQCV
231
3,488
0
07 Oct 2016
Direct Feedback Alignment Provides Learning in Deep Neural Networks
Arild Nøkland
ODL
208
462
0
06 Sep 2016
Equilibrium Propagation: Bridging the Gap Between Energy-Based Models and Backpropagation
B. Scellier
Yoshua Bengio
82
497
0
16 Feb 2016
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.5K
195,053
0
10 Dec 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
562
43,400
0
11 Feb 2015
Random feedback weights support learning in deep neural networks
Timothy Lillicrap
D. Cownden
D. Tweed
C. Akerman
ODL
81
171
0
02 Nov 2014
How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation
Yoshua Bengio
146
186
0
29 Jul 2014
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
554
16,907
0
20 Dec 2013
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