Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Gasparotto, Piero"'
Autor:
Prat, Alvaro, Aty, Hisham Abdel, Kamuntavičius, Gintautas, Paquet, Tanya, Norvaišas, Povilas, Gasparotto, Piero, Tal, Roy
We propose HydraScreen, a deep-learning approach that aims to provide a framework for more robust machine-learning-accelerated drug discovery. HydraScreen utilizes a state-of-the-art 3D convolutional neural network, designed for the effective represe
Externí odkaz:
http://arxiv.org/abs/2311.12814
Autor:
Gasparotto, Piero, Fitzner, Martin, Cox, Stephen J., Sosso, Gabriele Cesare, Michaelides, Angelos
Publikováno v:
Nanoscale, 2022
The structure of liquid water in the proximity of an interface can deviate significantly from that of bulk water, with surface-induced structural perturbations typically converging to bulk values at about ~1 nm from the interface. While these structu
Externí odkaz:
http://arxiv.org/abs/2202.13701
Autor:
Gasparotto, Piero, Fischer, Maria, Scopece, Daniele, Liedke, Maciej Oskar, Butterling, Maik, Wagner, Andreas, Yildirim, Oguz, Trant, Mathis, Passerone, Daniele, Hug, Hans J., Pignedoli, Carlo Antonio
Machine learning is changing how we design and interpret experiments in materials science. In this work, we show how unsupervised learning, combined with ab initio modeling, improves our understanding of structural metastability in multicomponent all
Externí odkaz:
http://arxiv.org/abs/2009.13186
We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed using the Gaussian approximation potential (GAP) methodology. The potential, named GAP-20, describes the properties of the bulk crystalline and amorph
Externí odkaz:
http://arxiv.org/abs/2006.13655
Autor:
Tribello, Gareth A., Gasparotto, Piero
This chapter discusses the way in which dimensionality reduction algorithms such as diffusion maps and sketch-map can be used to analyze molecular dynamics trajectories. The first part discusses how these various algorithms function, as well as pract
Externí odkaz:
http://arxiv.org/abs/1907.04170
Akademický článek
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Akademický článek
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Most of the current understanding of structure-property relations at the molecular and the supramolecular scales can be formulated in terms of the stability of and the interactions between a limited number of recurring structural motifs (e.g., H-bond
Externí odkaz:
http://arxiv.org/abs/1801.08633
Publikováno v:
Phys. Rev. Lett. 117(11), 115702 (2016)
Molecular crystals often exist in multiple competing polymorphs, showing significantly different physico-chemical properties. Computational crystal structure prediction is key to interpret and guide the search for the most stable or useful form: A re
Externí odkaz:
http://arxiv.org/abs/1609.04469
Publikováno v:
J. Chem. Theory Comput. 12 (4), 1953-1964 (2016)
The hydrogen-bond network of water is characterized by the presence of coordination defects relative to the ideal tetrahedral network of ice, whose fluctuations determine the static and time-dependent properties of the liquid. Because of topological
Externí odkaz:
http://arxiv.org/abs/1602.03577