Tommaso Salvatori : Publications
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[1]
A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks
Tommaso Salvatori‚ Yuhang Song‚ Yordan Yordanov‚ Beren Millidge‚ Lei Sha‚ Cornelius Emde‚ Zhenghua Xu‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 12th International Conference on Learning Representations‚ ICLR 2024‚ Vienna‚ Austria‚ 7–11 May 2024. May, 2024.
Details about A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks | BibTeX data for A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks
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[2]
Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation
Yuhang Song‚ Beren Millidge‚ Tommaso Salvatori‚ Thomas Lukasiewicz‚ Zhenghua Xu and Rafal Bogacz
In Nature Neuroscience. 2024.
Details about Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation | BibTeX data for Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation | Link to Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation
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[3]
Associative Memories in the Feature Space
Tommaso Salvatori‚ Beren Millidge‚ Yuhang Song‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 26th European Conference on Artificial Intelligence‚ ECAI 2023‚ Kraków‚ Poland‚ September 30 – October 5‚ 2023. IOS Press. September, 2023.
Details about Associative Memories in the Feature Space | BibTeX data for Associative Memories in the Feature Space
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[4]
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 and Rafal Bogacz
In Proceedings of the 11th International Conference on Learning Representations‚ ICLR 2023‚ Kigali‚ Rwanda‚ 1–5 May 2023. OpenReview.net. May, 2023.
Details about Backpropagation at the Infinitesimal Inference Limit of Energy−Based Models: Unifying Predictive Coding‚ Equilibrium Propagation‚ and Contrastive Hebbian Learning | BibTeX data for Backpropagation at the Infinitesimal Inference Limit of Energy−Based Models: Unifying Predictive Coding‚ Equilibrium Propagation‚ and Contrastive Hebbian Learning | Link to Backpropagation at the Infinitesimal Inference Limit of Energy−Based Models: Unifying Predictive Coding‚ Equilibrium Propagation‚ and Contrastive Hebbian Learning
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[5]
A Theoretical Framework for Inference and Learning in Predictive Coding Networks
Beren Millidge‚ Yuhang Song‚ Tommaso Salvatori‚ Thomas Lukasiewicz and Rafal Bogacz
In Proceedings of the 11th International Conference on Learning Representations‚ ICLR 2023‚ Kigali‚ Rwanda‚ 1–5 May 2023. OpenReview.net. May, 2023.
Details about A Theoretical Framework for Inference and Learning in Predictive Coding Networks | BibTeX data for A Theoretical Framework for Inference and Learning in Predictive Coding Networks | Link to A Theoretical Framework for Inference and Learning in Predictive Coding Networks
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[6]
Recurrent predictive coding models for associative memory employing covariance learning
Mufeng Tang‚ Tommaso Salvatori‚ Beren Millidge‚ Yuhang Song‚ Thomas Lukasiewicz and Rafal Bogacz
In PLOS Computational Biology. Vol. 19. No. 4. Pages e1010719. April, 2023.
Details about Recurrent predictive coding models for associative memory employing covariance learning | BibTeX data for Recurrent predictive coding models for associative memory employing covariance learning | Link to Recurrent predictive coding models for associative memory employing covariance learning
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[7]
Mathematical Capabilities of ChatGPT
Simon Frieder‚ Luca Pinchetti‚ Alexis Chevalier‚ Ryan−Rhys Griffiths‚ Tommaso Salvatori‚ Thomas Lukasiewicz‚ Philipp Christian Petersen and Julius Berner
In Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 3‚ NeurIPS Datasets and Benchmarks 2023‚ December 2023. December, 2023.
Details about Mathematical Capabilities of ChatGPT | BibTeX data for Mathematical Capabilities of ChatGPT
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[8]
Universal Hopfield Networks: A General Framework for Single−Shot Associative Memory Models
Beren Millidge‚ Tommaso Salvatori‚ Yuhang Song‚ Thomas Lukasiewicz and Rafal Bogacz
In Kamalika Chaudhuri‚ Stefanie Jegelka‚ Le Song‚ Csaba Szepesvari‚ Gang Niu and Sivan Sabato, editors, Proceedings of the 39th International Conference on Machine Learning‚ ICML 2022‚ Baltimore‚ Maryland‚ USA‚ 17−23 July 2022. Vol. 162 of Proceedings of Machine Learning Research. Pages 15561–15583. PMLR. July, 2022.
Details about Universal Hopfield Networks: A General Framework for Single−Shot Associative Memory Models | BibTeX data for Universal Hopfield Networks: A General Framework for Single−Shot Associative Memory Models | Link to Universal Hopfield Networks: A General Framework for Single−Shot Associative Memory Models
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[9]
Predictive Coding: Towards a Future of Deep Learning Beyond Backpropagation?
Beren Millidge‚ Tommaso Salvatori‚ Yuhang Song‚ Rafal Bogacz and Thomas Lukasiewicz
In Luc De Raedt, editor, Proceedings of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence‚ IJCAI−ECAI 2022‚ Survey Track‚ Vienna‚ Austria‚ July 23−29‚ 2022. Pages 5538–5545. IJCAI/AAAI Press. July, 2022.
Details about Predictive Coding: Towards a Future of Deep Learning Beyond Backpropagation? | BibTeX data for Predictive Coding: Towards a Future of Deep Learning Beyond Backpropagation? | Link to Predictive Coding: Towards a Future of Deep Learning Beyond Backpropagation?
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[10]
Reverse Differentiation via Predictive Coding
Tommaso Salvatori‚ Yuhang Song‚ Zhenghua Xu‚ Thomas Lukasiewicz and Rafal Bogacz
In Proceedings of the 36th AAAI Conference on Artificial Intelligence‚ AAAI 2022‚ Vancouver‚ BC‚ Canada‚ February 22 – March 1‚ 2022. Pages 8150–8158. AAAI Press. February, 2022.
Details about Reverse Differentiation via Predictive Coding | BibTeX data for Reverse Differentiation via Predictive Coding | Link to Reverse Differentiation via Predictive Coding
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[11]
Predictive Coding Beyond Gaussian Distributions
Luca Pinchetti‚ Tommaso Salvatori‚ Yordan Yordanov‚ Beren Millidge‚ Yuhang Song and Thomas Lukasiewicz
In Proceedings of the 36th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2022‚ New Orleans‚ Louisiana‚ USA. Pages 1280–1293. November, 2022.
Details about Predictive Coding Beyond Gaussian Distributions | BibTeX data for Predictive Coding Beyond Gaussian Distributions | Link to Predictive Coding Beyond Gaussian Distributions
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[12]
Learning on Arbitrary Graph Topologies via Predictive Coding
Tommaso Salvatori‚ Luca Pinchetti‚ Beren Millidge‚ Yuhang Song‚ Tianyi Bao‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 36th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2022‚ New Orleans‚ Louisiana‚ USA. Pages 38232–38244. November, 2022.
Details about Learning on Arbitrary Graph Topologies via Predictive Coding | BibTeX data for Learning on Arbitrary Graph Topologies via Predictive Coding | Link to Learning on Arbitrary Graph Topologies via Predictive Coding
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[13]
Associative Memories via Predictive Coding
Tommaso Salvatori‚ Yuhang Song‚ Yujian Hong‚ Simon Frieder‚ Lei Sha‚ Zhenghua Xu‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 35th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2021. December, 2021.
Details about Associative Memories via Predictive Coding | BibTeX data for Associative Memories via Predictive Coding | Link to Associative Memories via Predictive Coding
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[14]
BoxE: A Box Embedding Model for Knowledge Base Completion
Ralph Abboud‚ İsmail İlkan Ceylan‚ Thomas Lukasiewicz and Tommaso Salvatori
In Proceedings of the 34th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2020‚ December 6–12‚ 2020. December, 2020.
Details about BoxE: A Box Embedding Model for Knowledge Base Completion | BibTeX data for BoxE: A Box Embedding Model for Knowledge Base Completion | Link to BoxE: A Box Embedding Model for Knowledge Base Completion