Neural network

Applied sciences
Information engineering
Apprentissage automatique
Réseau de neurones artificiels

Publications associées (1 000)

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Publications associées (1 000)

A new age in protein design empowered by deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Hamed Khakzad, Casper Alexander Goverde, Arne Schneuing, Ilia Igashov

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

Cambridge2023

Towards learning-based image compression for storage on DNA support

Touradj Ebrahimi, Michela Testolina

The demand for data storage has grown exponentially over the past decades. Current archival solutions have significant shortcomings, such as high resource requirements and a lack of sufficient longevity. In contrast, research on DNA-based storage has been ...

2023

Deep Learning for 3D Surface Modelling and Reconstruction

Benoît Alain René Guillard

In recent years, there has been a significant revolution in the field of deep learning, which has demonstrated its effectiveness in automatically capturing intricate patterns from large datasets. However, the majority of these successes in Computer Vision ...

EPFL2023

Lightning is directly or indirectly responsible for significant human casualties and property damage worldwide. A timely prediction of its occurrence can enable authorities and the public to take necessary precautionary actions resulting in diminishing the ...

Basel2023

Exploration-based model learning with self-attention for risk-sensitive robot control

Sudong Lee

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

2023

Robust Training and Verification of Deep Neural Networks

Fabian Ricardo Latorre Gomez

According to the proposed Artificial Intelligence Act by the European Comission (expected to pass at the end of 2023), the class of High-Risk AI Systems (Title III) comprises several important applications of Deep Learning like autonomous driving vehicles ...

EPFL2023

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Hoboken2023

Self-correcting quantum many-body control using reinforcement learning with tensor networks

Friederike Metz

Quantum many-body control is a central milestone en route to harnessing quantum technologies. However, the exponential growth of the Hilbert space dimension with the number of qubits makes it challenging to classically simulate quantum many-body systems an ...

NATURE PORTFOLIO2023

Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

Matthias Wolf, Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Srikanth Ramaswamy, Michael Reimann, Daniel Keller, Werner Alfons Hilda Van Geit, James Gonzalo King, Pramod Shivaji Kumbhar, Alexis Arnaudon, Jean-Denis Georges Emile Courcol, Rajnish Ranjan, Armando Romani, András Ecker, Michael Emiel Gevaert, Vishal Sood, Sirio Bolaños Puchet, James Bryden Isbister, Judit Planas Carbonell, Daniela Egas Santander, Maria Reva, Genrich Ivaska, Natali Barros Zulaica, Mustafa Anil Tuncel, Christoph Pokorny, Elvis Boci, Jorge Blanco Alonso, Aleksandra Zuzanna Teska, Darshan Mandge, Polina Litvak, Gianluca Ficarelli, Weina Ji, Giuseppe Chindemi, Christian Andreas Rössert, Omar Awile, Joni Henrikki Herttuainen, Samuel Lieven D. Lapere, Thomas Brice Delemontex, Tanguy Pierre Louis Damart, Alexander Dietz

In recent years, large-scale computational models of the cortex have emerged as a powerful way to study the multi-scale mechanisms of neural processing. However, due to computational costs and difficulty of parameterization, detailed biophysical reconstruc ...

2023

A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients

Meritxell Bach Cuadra, Tobias Kober, Bénédicte Marie Maréchal, Cristina Granziera, Muhamed Barakovic, Lester Melie Garcia, Ricardo Alberto Corredor Jerez, Po-Jui Lu

BackgroundDetecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan-PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarge ...

WILEY2023

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