default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDRafal Bogacz
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c19]Tommaso Salvatori, Yuhang Song, Yordan Yordanov, Beren Millidge, Lei Sha, Cornelius Emde, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz:
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks. ICLR 2024- [i13]Tommaso Salvatori, Beren Millidge, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories in the Feature Space. CoRR abs/2402.10814 (2024) - [i12]Luca Pinchetti, Chang Qi, Oleh Lokshyn, Gaspard Olivers, Cornelius Emde, Mufeng Tang, Amine M'Charrak, Simon Frieder, Bayar Menzat, Rafal Bogacz, Thomas Lukasiewicz, Tommaso Salvatori:
Benchmarking Predictive Coding Networks - Made Simple. CoRR abs/2407.01163 (2024) - 2023
- [j31]Mufeng Tang, Tommaso Salvatori, Beren Millidge, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz
:
Recurrent predictive coding models for associative memory employing covariance learning. PLoS Comput. Biol. 19(4) (2023) - [c18]Tommaso Salvatori, Beren Millidge, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories in the Feature Space. ECAI 2023: 2065-2072 - [c17]Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz:
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning. ICLR 2023 - [c16]Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz:
A Theoretical Framework for Inference and Learning in Predictive Coding Networks. ICLR 2023 - [c15]Mufeng Tang, Helen Barron, Rafal Bogacz:
Sequential Memory with Temporal Predictive Coding. NeurIPS 2023 - [i11]Mufeng Tang, Helen Barron, Rafal Bogacz:
Sequential Memory with Temporal Predictive Coding. CoRR abs/2305.11982 (2023) - 2022
- [j30]Germain Lefebvre, Christopher Summerfield, Rafal Bogacz:
A Normative Account of Confirmation Bias During Reinforcement Learning. Neural Comput. 34(2): 307-337 (2022) - [j29]Moritz Möller, Sanjay G. Manohar, Rafal Bogacz:
Uncertainty-guided learning with scaled prediction errors in the basal ganglia. PLoS Comput. Biol. 18(5) (2022) - [c14]Tommaso Salvatori, Yuhang Song, Zhenghua Xu, Thomas Lukasiewicz, Rafal Bogacz:
Reverse Differentiation via Predictive Coding. AAAI 2022: 8150-8158 - [c13]Beren Millidge, Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz:
Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Models. ICML 2022: 15561-15583 - [c12]Beren Millidge, Tommaso Salvatori, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation? IJCAI 2022: 5538-5545 - [c11]Tommaso Salvatori, Luca Pinchetti, Beren Millidge, Yuhang Song, Tianyi Bao, Rafal Bogacz, Thomas Lukasiewicz:
Learning on Arbitrary Graph Topologies via Predictive Coding. NeurIPS 2022 - [i10]Tommaso Salvatori, Luca Pinchetti, Beren Millidge, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Learning on Arbitrary Graph Topologies via Predictive Coding. CoRR abs/2201.13180 (2022) - [i9]Beren Millidge, Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz:
Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Models. CoRR abs/2202.04557 (2022) - [i8]Beren Millidge, Tommaso Salvatori, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation? CoRR abs/2202.09467 (2022) - [i7]Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz:
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning. CoRR abs/2206.02629 (2022) - [i6]Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz:
A Theoretical Framework for Inference and Learning in Predictive Coding Networks. CoRR abs/2207.12316 (2022) - [i5]Tommaso Salvatori, Yuhang Song, Beren Millidge, Zhenghua Xu, Lei Sha, Cornelius Emde, Rafal Bogacz, Thomas Lukasiewicz:
Incremental Predictive Coding: A Parallel and Fully Automatic Learning Algorithm. CoRR abs/2212.00720 (2022) - 2021
- [j28]Benoit Duchet, Filippo Ghezzi, Gihan Weerasinghe, Gerd Tinkhauser, Andrea A. Kühn, Peter Brown, Christian Bick, Rafal Bogacz:
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. 17(7) (2021) - [j27]Moritz Möller, Jan Grohn, Sanjay G. Manohar, Rafal Bogacz:
An association between prediction errors and risk-seeking: Theory and behavioral evidence. PLoS Comput. Biol. 17(7) (2021) - [j26]Gihan Weerasinghe, Benoit Duchet, Christian Bick, Rafal Bogacz:
Optimal closed-loop deep brain stimulation using multiple independently controlled contacts. PLoS Comput. Biol. 17(8) (2021) - [c10]Tommaso Salvatori, Yuhang Song, Yujian Hong, Lei Sha, Simon Frieder, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories via Predictive Coding. NeurIPS 2021: 3874-3886 - [i4]Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz, Zhenghua Xu:
Predictive Coding Can Do Exact Backpropagation on Convolutional and Recurrent Neural Networks. CoRR abs/2103.03725 (2021) - [i3]Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz, Zhenghua Xu:
Predictive Coding Can Do Exact Backpropagation on Any Neural Network. CoRR abs/2103.04689 (2021) - [i2]Mayela Zamora, Sebastian Meller, Filip Kajin, James J. Sermon, Robert Toth, Moaad Benjaber, Derk-Jan Dijk, Rafal Bogacz, Gregory A. Worrell, Antonio Valentín, Benoit Duchet, Holger A. Volk, Timothy Denison:
Embedding digital chronotherapy into medical devices - A canine case study in controlling status epilepticus through multi-scale rhythmic brain stimulation. CoRR abs/2107.02993 (2021) - [i1]Tommaso Salvatori, Yuhang Song, Yujian Hong, Simon Frieder, Lei Sha, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories via Predictive Coding. CoRR abs/2109.08063 (2021) - 2020
- [j25]Maaike M. H. van Swieten, Rafal Bogacz:
Modeling the effects of motivation on choice and learning in the basal ganglia. PLoS Comput. Biol. 16(5) (2020) - [c9]Yuhang Song, Thomas Lukasiewicz, Zhenghua Xu, Rafal Bogacz:
Can the Brain Do Backpropagation? - Exact Implementation of Backpropagation in Predictive Coding Networks. NeurIPS 2020
2010 – 2019
- 2019
- [j24]Moritz Möller, Rafal Bogacz:
Learning the payoffs and costs of actions. PLoS Comput. Biol. 15(2) (2019) - [j23]Gihan Weerasinghe, Benoit Duchet, Hayriye Cagnan, Peter Brown, Christian Bick, Rafal Bogacz:
Predicting the effects of deep brain stimulation using a reduced coupled oscillator model. PLoS Comput. Biol. 15(8) (2019) - 2018
- [j22]Friederike Leimbach, Dejan Georgiev, Vladimir Litvak, Chrystalina Antoniades, Patricia Limousin, Marjan Jahanshahi, Rafal Bogacz:
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. 30(6) (2018) - [c8]Eduardo Martin Moraud, Gerd Tinkhauser, Mayank Agrawal, Peter Brown, Rafal Bogacz:
Predicting beta bursts from local field potentials to improve closed-loop DBS paradigms in Parkinson's patients. EMBC 2018: 3766-3796 - 2017
- [j21]Nils Kurzawa, Christopher Summerfield, Rafal Bogacz:
Neural Circuits Trained with Standard Reinforcement Learning Can Accumulate Probabilistic Information during Decision Making. Neural Comput. 29(2): 368-393 (2017) - [j20]James C. R. Whittington, Rafal Bogacz:
An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity. Neural Comput. 29(5): 1229-1262 (2017) - 2016
- [j19]Rafal Bogacz, Eduardo Martin Moraud, Azzedine Abdi, Peter J. Magill, Jérôme Baufreton:
Properties of Neurons in External Globus Pallidus Can Support Optimal Action Selection. PLoS Comput. Biol. 12(7) (2016) - [j18]John G. Mikhael, Rafal Bogacz:
Learning Reward Uncertainty in the Basal Ganglia. PLoS Comput. Biol. 12(9) (2016) - 2015
- [j17]John Grogan, Rafal Bogacz, Demitra Tsivos, Alan L. Whone, Elizabeth J. Coulthard:
Dopamine and Consolidation of Episodic Memory: Timing Is Everything. J. Cogn. Neurosci. 27(10): 2035-2050 (2015) - [j16]Alex Pavlides, Stephen John Hogan, Rafal Bogacz:
Computational Models Describing Possible Mechanisms for Generation of Excessive Beta Oscillations in Parkinson's Disease. PLoS Comput. Biol. 11(12) (2015) - 2014
- [r2]Rafal Bogacz:
Basal Ganglia: Beta Oscillations. Encyclopedia of Computational Neuroscience 2014 - [r1]Rafal Bogacz:
Speed-Accuracy Trade-Off. Encyclopedia of Computational Neuroscience 2014 - 2012
- [j15]Kevin Lloyd, Nadine Becker, Matthew W. Jones, Rafal Bogacz:
Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats. Frontiers Comput. Neurosci. 6: 87 (2012) - 2011
- [j14]Rafal Bogacz, Tobias Larsen:
Integration of Reinforcement Learning and Optimal Decision-Making Theories of the Basal Ganglia. Neural Comput. 23(4): 817-851 (2011) - [j13]Andrew Lulham, Rafal Bogacz, Simon Vogt, Malcolm W. Brown:
An Infomax Algorithm Can Perform Both Familiarity Discrimination and Feature Extraction in a Single Network. Neural Comput. 23(4): 909-926 (2011) - [c7]Alejo J. Nevado-Holgado, John R. Terry, Rafal Bogacz:
Bifurcation analysis points towards the source of beta neuronal oscillations in Parkinson's disease. CDC/ECC 2011: 6492-6497 - 2010
- [j12]Jiaxiang Zhang, Rafal Bogacz:
Optimal Decision Making on the Basis of Evidence Represented in Spike Trains. Neural Comput. 22(5): 1113-1148 (2010) - [j11]Tobias Larsen, David S. Leslie, Edmund J. Collins, Rafal Bogacz:
Posterior Weighted Reinforcement Learning with State Uncertainty. Neural Comput. 22(5): 1149-1179 (2010) - [j10]Paul A. Howard-Jones, Rafal Bogacz, Jee H. Yoo, Ute Leonards, Skevi Demetriou:
The neural mechanisms of learning from competitors. NeuroImage 53(2): 790-799 (2010) - [j9]Tobias Larsen, Rafal Bogacz:
Initiation and termination of integration in a decision process. Neural Networks 23(3): 322-333 (2010)
2000 – 2009
- 2008
- [c6]Pete Trimmer, John McNamara, Alasdair Houston, James A. R. Marshall, Liz Paul, Rafal Bogacz, Mike Mendl:
Mammalian decisions. ALIFE 2008: 811 - 2007
- [j8]Rafal Bogacz, Kevin N. Gurney:
The Basal Ganglia and Cortex Implement Optimal Decision Making Between Alternative Actions. Neural Comput. 19(2): 442-477 (2007) - [j7]Rafal Bogacz:
Optimal decision network with distributed representation. Neural Networks 20(5): 564-576 (2007) - 2005
- [j6]Philip Holmes, Eric Shea-Brown, Jeff Moehlis, Rafal Bogacz, Juan Gao, Gary Aston-Jones, Ed Clayton, Janusz Rajkowski, Jonathan D. Cohen:
Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 88-A(10): 2496-2503 (2005) - [j5]Eric Brown, Juan Gao, Philip Holmes, Rafal Bogacz, Mark S. Gilzenrat, Jonathan D. Cohen:
Simple Neural Networks that Optimize Decisions. Int. J. Bifurc. Chaos 15(3): 803-826 (2005) - 2003
- [j4]Rafal Bogacz, Malcolm W. Brown:
An anti-Hebbian model of familiarity discrimination in the perirhinal cortex. Neurocomputing 52-54: 1-6 (2003) - 2002
- [j3]Rafal Bogacz, Malcolm W. Brown:
Capacity of perirhinal cortex network for recognising frequently repeating stimuli. Neurocomputing 44-46: 337-342 (2002) - 2001
- [b1]Rafal Bogacz:
Computational models of familiarity discrimination in the perirhinal cortex. University of Bristol, UK, 2001 - [j2]Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier:
Model of co-operation between recency, familiarity and novelty neurons in the perirhinal cortex. Neurocomputing 38-40: 1121-1126 (2001) - [j1]Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier:
Model of Familiarity Discrimination in the Perirhinal Cortex. J. Comput. Neurosci. 10(1): 5-23 (2001) - [c5]Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier:
A Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex. Emergent Neural Computational Architectures Based on Neuroscience 2001: 428-441 - 2000
- [c4]Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier:
Frequency-Based Error Back-Propagation in a Cortical Network. IJCNN (2) 2000: 211-216 - [c3]Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier:
Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images. NIPS 2000: 838-844
1990 – 1999
- 1998
- [c2]Rafal Bogacz, Christophe G. Giraud-Carrier:
A Novel Modular Neural Architecture for Rule-Based and Similarity-Based Reasoning. Hybrid Neural Systems 1998: 63-77 - [c1]Rafal Bogacz, Christophe G. Giraud-Carrier:
BRAINN: A Connectionist Approach to Symbolic Reasoning. NC 1998: 907-913
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:25 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
