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Predictive coding networks are neuroscience-inspired models with roots in both Bayesian statistics and neuroscience.
Predictive coding–I
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Karl Friston · 2003
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Karl Friston · 2005
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Karl Friston, James Kilner, and Lee Harrison · 2006
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Predictive coding approximates backprop along arbitrary computation graphs
Beren Millidge, Alexander Tschantz, and Christopher L Buckley · 2006
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Sensitivity derivatives for flexible sensorimotor learning
Mohammed. Abdelghani, Timothy. Lillicrap, and Douglas Tweed · 2008
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DEM: A variational treatment of dynamic systems
Karl J. Friston, N. Trujillo-Barreto, and Jean Daunizeau · 2008
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The free-energy principle: A unified brain theory?
Karl Friston · 2010
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Yann LeCun and Corinna Cortes · 2010
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Relaxing the constraints on predictive coding models
Beren Millidge, Alexander Tschantz, Anil Seth, and Christopher L Buckley · 2010
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng · 2011
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ImageNet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson · 2013
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Posterior calibration and exploratory analysis for natural language processing models
Khanh Nguyen and Brendan T. O’Connor · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 2016
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Active inference and learning
Karl Friston, Thomas FitzGerald, Francesco Rigoli, Philipp Schwartenbeck, Giovanni Pezzulo, et al · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Random synaptic feedback weights support error backpropagation for deep learning
Timothy P Lillicrap, Daniel Cownden, Douglas B Tweed, and Colin J Akerman · 2016
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Mastering the game of Go with deep neural networks and tree search
David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis · 2016
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A tutorial on the free-energy framework for modelling perception and learning
Rafal Bogacz · 2017
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The free energy principle for action and perception: A mathematical review
Chris Buckley, Chang Kim, Simon McGregor, and Anil Seth · 2017
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Simulating a primary visual cortex at the front of CNNs improves robustness to image perturbations
Joel Dapello, Tiago Marques, Martin Schrimpf, Franziska Geiger, David Cox, and James J DiCarlo · 2020
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Equilibrium propagation with continual weight updates
Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, and Benjamin Scellier · 2020
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Training end-to-end analog neural networks with equilibrium propagation
Jack Kendall, Ross Pantone, Kalpana Manickavasagam, Yoshua Bengio, and Benjamin Scellier · 2020
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The neural coding framework for learning generative models
Alex Ororbia and Daniel Kifer · 2020
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Continual learning of recurrent neural networks by locally aligning distributed representations
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Learning to adapt by minimizing discrepancy
II Ororbia, G. Alexander, Patrick Haffner, David Reitter, and C. Lee Giles · 2017
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Equilibrium propagation: Bridging the gap between energy-based models and backpropagation
Benjamin Scellier and Yoshua Bengio · 2017
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Mastering the game of Go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, and Demis Hassabis · 2017
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An approximation of the error backpropagation algorithm in a predictive coding network with local Hebbian synaptic plasticity
James C. R. Whittington and Rafal Bogacz · 2017
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SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson · 2018
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Alexander Ororbia, Ankur Mali, C. Lee Giles, and Daniel Kifer · 2020
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Can the brain do backpropagation? — Exact implementation of backpropagation in predictive coding networks
Yuhang Song, Thomas Lukasiewicz, Zhenghua Xu, and Rafal Bogacz · 2020
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Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics
Bhavin Choksi, Milad Mozafari, Callum Biggs O’May, Benjamin Ador, Andrea Alamia, and Rufin VanRullen · 2021
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Predictive coding: A theoretical and experimental review
Beren Millidge, Anil Seth, and Christopher L Buckley · 2021
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Associative memories via predictive coding
Tommaso Salvatori, Yuhang Song, Yujian Hong, Lei Sha, Simon Frieder, Zhenghua Xu, Rafal Bogacz, and Thomas Lukasiewicz · 2021
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A theoretical framework for inference learning
Nick Alonso, Beren Millidge, Jeffrey Krichmar, and Emre O Neftci · 2022
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Human-level play in the game of diplomacy by combining language models with strategic reasoning
Anton Bakhtin, Noam Brown, Emily Dinan, Gabriele Farina, Colin Flaherty, Daniel Fried, Andrew Goff, Jonathan Gray, Hengyuan Hu, et al · 2022
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Robust graph representation learning via predictive coding
Billy Byiringiro, Tommaso Salvatori, and Thomas Lukasiewicz · 2022
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Designing ecosystems of intelligence from first principles
Karl J Friston, Maxwell JD Ramstead, Alex B Kiefer, Alexander Tschantz, Christopher L Buckley, Mahault Albarracin, Riddhi J Pitliya, Conor Heins, Brennan Klein, Beren Millidge, et al · 2022
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Hebbian deep learning without feedback
Adrien Journé, Hector Garcia Rodriguez, Qinghai Guo, and Timoleon Moraitis · 2022
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Lifelong neural predictive coding: Learning cumulatively online without forgetting
Alex Ororbia, Ankur Mali, C Lee Giles, and Daniel Kifer · 2022
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The neural coding framework for learning generative models
Alexander Ororbia and Daniel Kifer · 2022
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Predictive coding beyond Gaussian distributions
Luca Pinchetti, Tommaso Salvatori, Beren Millidge, Yuhang Song, Yordan Yordanov, and Thomas Lukasiewicz · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
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Inferring neural activity before plasticity: A foundation for learning beyond backpropagation
Yuhang Song, Beren Gray Millidge, Tommaso Salvatori, Thomas Lukasiewicz, Zhenghua Xu, and Rafal Bogacz · 2022
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Toward next-generation artificial intelligence: catalyzing the neuroai revolution
Anthony Zador, Blake Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew Botvinick, Dmitri Chklovskii, Anne Churchland, Claudia Clopath, et al · 2022
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Brain-inspired computational intelligence via predictive coding
Tommaso Salvatori, Ankur Mali, Christopher L Buckley, Thomas Lukasiewicz, Rajesh PN Rao, Karl Friston, and Alexander Ororbia · 2023
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Recurrent predictive coding models for associative memory employing covariance learning
Mufeng Tang, Tommaso Salvatori, Beren Millidge, Yuhang Song, Thomas Lukasiewicz, and Rafal Bogacz · 2023
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