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Nature Materials
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November 13, 2025
Memristors for Bayesian in-memory computing
Thomas Dalgaty, Elisa Vianello, Damien Querlioz
Frontiers in Neuroscience
|
March 12, 2021
Bio-Inspired Architectures Substantially Reduce the Memory Requirements of Neural Network Models
Thomas Dalgaty, John P Miller, Elisa Vianello, et al.
Sensors (Basel, Switzerland)
|
February 28, 2023
End-to-End Implementation of a Convolutional Neural Network on a 3D-Integrated Image Sensor with Macropixel Array
Maria Lepecq, Thomas Dalgaty, William Fabre, et al.
Current Opinion in Insect Science
|
December 17, 2018
Insect-inspired neuromorphic computing
Thomas Dalgaty, Elisa Vianello, Barbara De Salvo, et al.
Nature Communications
|
November 1, 2022
Author Correction: Self-organization of an inhomogeneous memristive hardware for sequence learning
Melika Payvand, Filippo Moro, Kumiko Nomura, et al.
Nature Communications
|
October 2, 2022
Self-organization of an inhomogeneous memristive hardware for sequence learning
Melika Payvand, Filippo Moro, Kumiko Nomura, et al.
Nature Communications
|
October 31, 2025
Bayesian continual learning and forgetting in neural networks
Djohan Bonnet, Kellian Cottart, Tifenn Hirtzlin, et al.
Nature Communications
|
January 3, 2024
Mosaic: in-memory computing and routing for small-world spike-based neuromorphic systems
Thomas Dalgaty, Filippo Moro, Yiğit Demirağ, et al.
Small (Weinheim an Der Bergstrasse, Germany)
|
June 9, 2018
Monolayer Graphene Coupled to a Flexible Plasmonic Nanograting for Ultrasensitive Strain Monitoring
Raphael F Tiefenauer, Thomas Dalgaty, Tobias Keplinger, et al.
Nature Communications
|
November 20, 2023
Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks
Djohan Bonnet, Tifenn Hirtzlin, Atreya Majumdar, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 11) with videos related to
Sort By:
Page
of 2
Nature Materials
|
November 13, 2025
Memristors for Bayesian in-memory computing
Thomas Dalgaty, Elisa Vianello, Damien Querlioz
Frontiers in Neuroscience
|
March 12, 2021
Bio-Inspired Architectures Substantially Reduce the Memory Requirements of Neural Network Models
Thomas Dalgaty, John P Miller, Elisa Vianello, et al.
Sensors (Basel, Switzerland)
|
February 28, 2023
End-to-End Implementation of a Convolutional Neural Network on a 3D-Integrated Image Sensor with Macropixel Array
Maria Lepecq, Thomas Dalgaty, William Fabre, et al.
Current Opinion in Insect Science
|
December 17, 2018
Insect-inspired neuromorphic computing
Thomas Dalgaty, Elisa Vianello, Barbara De Salvo, et al.
Nature Communications
|
November 1, 2022
Author Correction: Self-organization of an inhomogeneous memristive hardware for sequence learning
Melika Payvand, Filippo Moro, Kumiko Nomura, et al.
Nature Communications
|
October 2, 2022
Self-organization of an inhomogeneous memristive hardware for sequence learning
Melika Payvand, Filippo Moro, Kumiko Nomura, et al.
Nature Communications
|
October 31, 2025
Bayesian continual learning and forgetting in neural networks
Djohan Bonnet, Kellian Cottart, Tifenn Hirtzlin, et al.
Nature Communications
|
January 3, 2024
Mosaic: in-memory computing and routing for small-world spike-based neuromorphic systems
Thomas Dalgaty, Filippo Moro, Yiğit Demirağ, et al.
Small (Weinheim an Der Bergstrasse, Germany)
|
June 9, 2018
Monolayer Graphene Coupled to a Flexible Plasmonic Nanograting for Ultrasensitive Strain Monitoring
Raphael F Tiefenauer, Thomas Dalgaty, Tobias Keplinger, et al.
Nature Communications
|
November 20, 2023
Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks
Djohan Bonnet, Tifenn Hirtzlin, Atreya Majumdar, et al.
Page
of 2