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E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

Nature communications, 2022-05, Vol.13 (1), p.2453-2453, Article 2453

2022

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A recipe for cracking the quantum scaling limit with machine learned electron densities

Machine learning: science and technology, 2023-03, Vol.4 (1), p.15027

2023

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Asymptotic learning curves of kernel methods: empirical data versus teacher-student paradigm

Journal of statistical mechanics, 2020-12, Vol.2020 (12), p.124001

2020

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Landscape and training regimes in deep learning

Physics reports, 2021-08, Vol.924, p.1-18

2021

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Disentangling feature and lazy training in deep neural networks

Journal of statistical mechanics, 2020-11, Vol.2020 (11), p.113301

2020

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Geometric compression of invariant manifolds in neural networks

Journal of statistical mechanics, 2021-04, Vol.2021 (4), p.44001

2021

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Scaling description of generalization with number of parameters in deep learning

Journal of statistical mechanics, 2020-02, Vol.2020 (2), p.23401

2020

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Jamming transition as a paradigm to understand the loss landscape of deep neural networks

Physical review. E, 2019-07, Vol.100 (1-1), p.012115-012115, Article 012115

2019

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Relative stability toward diffeomorphisms indicates performance in deep nets

Journal of statistical mechanics, 2022-11, Vol.2022 (11), p.114013

2022

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The strong gravitational lens finding challenge

Astronomy and astrophysics (Berlin), 2019, Vol.625, p.A119

2019

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Comparing dynamics: deep neural networks versus glassy systems

Journal of statistical mechanics, 2019-12, Vol.2019 (12), p.124013

2019

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Thermal solar collector with VO2 absorber coating and V1-xWxO2 thermochromic glazing – Temperature matching and triggering

Solar energy, 2014-12, Vol.110, p.151-159

2014

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Relative stability toward diffeomorphisms indicates performance in deep nets This article is an updated version of: Petrini L, Favero A, Geiger M and Wyart M 2021 Relative stability toward diffeomorphisms indicates performance in deep nets Advances in Neural Information Processing Systems vol 34 ed M Ranzato, A Beygelzimer, Y Dauphin, P S Liang and J Wortman Vaughan (New York: Curran Associates) pp 8727–39

Journal of statistical mechanics, 2022-11, Vol.2022 (11)

2022

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Artificial intelligence in neurology: opportunities, challenges, and policy implications

Journal of neurology, 2024-05, Vol.271 (5), p.2258-2273

2024

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Thermal solar collector with VO2 absorber coating and V 1 - x W x O 2 thermochromic glazing – Temperature matching and triggering

Solar energy, 2014-12, Vol.110, p.151-159

2014

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Thermal solar collector with VO^sub 2^ absorber coating and V^sub 1-x^ W^sub x^ O^sub 2^ thermochromic glazing - Temperature matching and triggering

Solar energy, 2014-12, Vol.110, p.151

2014

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Comparing dynamics: deep neural networks versus glassy systemsThis article is an updated version of a paper presented at ICML 2018, and is present in the following informal collection of proceedings: 2018 Proceedings Of Machine Learning Research 80 324-333

Journal of statistical mechanics, 2019-12, Vol.2019 (12)

2019

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Bringing the ocean into the laboratory to probe the chemical complexity of sea spray aerosol

Proceedings of the National Academy of Sciences - PNAS, 2013-05, Vol.110 (19), p.7550-7555

2013

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A transcription factor atlas of directed differentiation

Cell, 2023-01, Vol.186 (1), p.209-229.e26

2023

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Oxide– and Silicate–Water Interfaces and Their Roles in Technology and the Environment

Chemical reviews, 2023-05, Vol.123 (10), p.6413-6544

2023

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Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia

International journal of environmental research and public health, 2022-06, Vol.19 (11), p.6937

2022

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A transcription factor atlas of directed differentiation

Cell, 2024-06, Vol.187 (12), p.3161-3161

2024

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Theory-inspired machine learning—towards a synergy between knowledge and data

Welding in the world, 2022-07, Vol.66 (7), p.1291-1304

2022

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Experimental investigation of a variable compression ratio system applied to a gasoline passenger car engine

Energy conversion and management, 2019-03, Vol.183, p.753-763

2019

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E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

A recipe for cracking the quantum scaling limit with machine learned electron densities

Asymptotic learning curves of kernel methods: empirical data versus teacher-student paradigm

Landscape and training regimes in deep learning

Disentangling feature and lazy training in deep neural networks

Geometric compression of invariant manifolds in neural networks

Scaling description of generalization with number of parameters in deep learning

Jamming transition as a paradigm to understand the loss landscape of deep neural networks

Relative stability toward diffeomorphisms indicates performance in deep nets

The strong gravitational lens finding challenge

Comparing dynamics: deep neural networks versus glassy systems

Thermal solar collector with VO2 absorber coating and V1-xWxO2 thermochromic glazing – Temperature matching and triggering

Artificial intelligence in neurology: opportunities, challenges, and policy implications

Thermal solar collector with VO2 absorber coating and V 1 - x W x O 2 thermochromic glazing – Temperature matching and triggering

Thermal solar collector with VO^sub 2^ absorber coating and V^sub 1-x^ W^sub x^ O^sub 2^ thermochromic glazing - Temperature matching and triggering

Comparing dynamics: deep neural networks versus glassy systemsThis article is an updated version of a paper presented at ICML 2018, and is present in the following informal collection of proceedings: 2018 Proceedings Of Machine Learning Research 80 324-333

Bringing the ocean into the laboratory to probe the chemical complexity of sea spray aerosol

A transcription factor atlas of directed differentiation

Oxide– and Silicate–Water Interfaces and Their Roles in Technology and the Environment

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia

Towards a multisensor station for automated biodiversity monitoring

A transcription factor atlas of directed differentiation

Theory-inspired machine learning—towards a synergy between knowledge and data

Experimental investigation of a variable compression ratio system applied to a gasoline passenger car engine

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