Rafal Bogacz

Orcid: 0000-0002-8994-1661

According to our database1, Rafal Bogacz authored at least 59 papers between 1998 and 2024.

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Bibliography

2024
Benchmarking Predictive Coding Networks - Made Simple.
CoRR, 2024

A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Recurrent predictive coding models for associative memory employing covariance learning.
PLoS Comput. Biol., 2023

Sequential Memory with Temporal Predictive Coding.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Theoretical Framework for Inference and Learning in Predictive Coding Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Associative Memories in the Feature Space.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
Uncertainty-guided learning with scaled prediction errors in the basal ganglia.
PLoS Comput. Biol., 2022

A Normative Account of Confirmation Bias During Reinforcement Learning.
Neural Comput., 2022

Incremental Predictive Coding: A Parallel and Fully Automatic Learning Algorithm.
CoRR, 2022

Learning on Arbitrary Graph Topologies via Predictive Coding.
CoRR, 2022

Learning on Arbitrary Graph Topologies via Predictive Coding.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation?
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Models.
Proceedings of the International Conference on Machine Learning, 2022

Reverse Differentiation via Predictive Coding.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Optimal closed-loop deep brain stimulation using multiple independently controlled contacts.
PLoS Comput. Biol., 2021

An association between prediction errors and risk-seeking: Theory and behavioral evidence.
PLoS Comput. Biol., 2021

Average beta burst duration profiles provide a signature of dynamical changes between the ON and OFF medication states in Parkinson's disease.
PLoS Comput. Biol., 2021

Embedding digital chronotherapy into medical devices - A canine case study in controlling status epilepticus through multi-scale rhythmic brain stimulation.
CoRR, 2021

Predictive Coding Can Do Exact Backpropagation on Any Neural Network.
CoRR, 2021

Predictive Coding Can Do Exact Backpropagation on Convolutional and Recurrent Neural Networks.
CoRR, 2021

Associative Memories via Predictive Coding.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Modeling the effects of motivation on choice and learning in the basal ganglia.
PLoS Comput. Biol., 2020

Can the Brain Do Backpropagation? - Exact Implementation of Backpropagation in Predictive Coding Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Predicting the effects of deep brain stimulation using a reduced coupled oscillator model.
PLoS Comput. Biol., 2019

Learning the payoffs and costs of actions.
PLoS Comput. Biol., 2019

2018
Deep Brain Stimulation of the Subthalamic Nucleus Does Not Affect the Decrease of Decision Threshold during the Choice Process When There Is No Conflict, Time Pressure, or Reward.
J. Cogn. Neurosci., 2018

Predicting beta bursts from local field potentials to improve closed-loop DBS paradigms in Parkinson's patients.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2017
An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity.
Neural Comput., 2017

Neural Circuits Trained with Standard Reinforcement Learning Can Accumulate Probabilistic Information during Decision Making.
Neural Comput., 2017

2016
Learning Reward Uncertainty in the Basal Ganglia.
PLoS Comput. Biol., 2016

Properties of Neurons in External Globus Pallidus Can Support Optimal Action Selection.
PLoS Comput. Biol., 2016

2015
Computational Models Describing Possible Mechanisms for Generation of Excessive Beta Oscillations in Parkinson's Disease.
PLoS Comput. Biol., 2015

Dopamine and Consolidation of Episodic Memory: Timing Is Everything.
J. Cogn. Neurosci., 2015

2014
Speed-Accuracy Trade-Off.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Basal Ganglia: Beta Oscillations.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

2012
Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats.
Frontiers Comput. Neurosci., 2012

2011
An Infomax Algorithm Can Perform Both Familiarity Discrimination and Feature Extraction in a Single Network.
Neural Comput., 2011

Integration of Reinforcement Learning and Optimal Decision-Making Theories of the Basal Ganglia.
Neural Comput., 2011

Bifurcation analysis points towards the source of beta neuronal oscillations in Parkinson's disease.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
Initiation and termination of integration in a decision process.
Neural Networks, 2010

The neural mechanisms of learning from competitors.
NeuroImage, 2010

Optimal Decision Making on the Basis of Evidence Represented in Spike Trains.
Neural Comput., 2010

Posterior Weighted Reinforcement Learning with State Uncertainty.
Neural Comput., 2010

2008
Mammalian decisions.
Proceedings of the Eleventh International Conference on the Synthesis and Simulation of Living Systems, 2008

2007
Optimal decision network with distributed representation.
Neural Networks, 2007

The Basal Ganglia and Cortex Implement Optimal Decision Making Between Alternative Actions.
Neural Comput., 2007

2005
Simple Neural Networks that Optimize Decisions.
Int. J. Bifurc. Chaos, 2005

Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2005

2003
An anti-Hebbian model of familiarity discrimination in the perirhinal cortex.
Neurocomputing, 2003

2002
Capacity of perirhinal cortex network for recognising frequently repeating stimuli.
Neurocomputing, 2002

2001
Computational models of familiarity discrimination in the perirhinal cortex.
PhD thesis, 2001

Model of Familiarity Discrimination in the Perirhinal Cortex.
J. Comput. Neurosci., 2001

Model of co-operation between recency, familiarity and novelty neurons in the perirhinal cortex.
Neurocomputing, 2001

A Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex.
Proceedings of the Emergent Neural Computational Architectures Based on Neuroscience, 2001

2000
Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Frequency-Based Error Back-Propagation in a Cortical Network.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1998
BRAINN: A Connectionist Approach to Symbolic Reasoning.
Proceedings of the International ICSC / IFAC Symposium on Neural Computation (NC 1998), 1998

A Novel Modular Neural Architecture for Rule-Based and Similarity-Based Reasoning.
Proceedings of the Hybrid Neural Systems, 1998


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