Stefano Martiniani
Title
Cited by
Cited by
Year
Energy landscapes for machine learning
AJ Ballard, R Das, S Martiniani, D Mehta, L Sagun, JD Stevenson, ...
Physical Chemistry Chemical Physics 19 (20), 12585-12603, 2017
772017
The Mechanism of Iodine Reduction by TiO2 Electrons and the Kinetics of Recombination in Dye Sensitized Solar Cells
CE Richards, AY Anderson, S Martinani, CH Law, BC O'Regan
The Journal of Physical Chemistry Letters, 2012
702012
Superposition Enhanced Nested Sampling
S Martiniani, JD Stevenson, DJ Wales, D Frenkel
Physical Review X 4 (3), 031034, 2014
472014
Turning intractable counting into sampling: computing the configurational entropy of three-dimensional jammed packings
S Martiniani, KJ Schrenk, JD Stevenson, DJ Wales, D Frenkel
Physical Review E 93, 012906, 2016
382016
Quantifying Hidden Order out of Equilibrium
S Martiniani, PM Chaikin, D Levine
Physical Review X 9, 011031, 2019
372019
New insight into the regeneration kinetics of organic dye sensitised solar cells
S Martiniani, AY Anderson, CH Law, BC O'Regan, C Barolo
Chemical Communications 48 (18), 2406-2408, 2012
372012
Near-infrared absorbing squaraine dye with extended π conjugation for dye-sensitized solar cells
C Magistris, S Martiniani, N Barbero, J Park, C Benzi, A Anderson, ...
Renewable Energy 60, 672-678, 2013
362013
Numerical test of the Edwards conjecture shows that all packings are equally probable at jamming
S Martiniani, KJ Schrenk, K Ramola, B Chakraborty, D Frenkel
Nature Physics, 13, 848–851, 2017
26*2017
Exploiting the potential energy landscape to sample free energy
A Ballard, S Martiniani, JD Stevenson, S Somani, DJ Wales
WIREs computational molecular science, 2015
242015
Structural analysis of high-dimensional basins of attraction
S Martiniani, KJ Schrenk, JD Stevenson, DJ Wales, D Frenkel
Physical Review E 93 (3), 031301, 2016
132016
Monte Carlo sampling for stochastic weight functions
D Frenkel, KJ Schrenk, S Martiniani
Proceedings of the National Academy of Sciences 114 (27), 6924-6929, 2017
102017
Correlation lengths in the language of computable information
S Martiniani, Y Lemberg, PM Chaikin, D Levine
Physical Review Letters 125, 170601, 2020
12020
Vicsek Model by Time-Interlaced Compression: a Dynamical Computable Information Density
A Cavagna, PM Chaikin, D Levine, S Martiniani, A Puglisi, M Viale
arXiv preprint arXiv:2007.11322, 2020
12020
A method for the accurate determination of basins of attraction of jammed packings
P Suryadevara, S Martiniani
Bulletin of the American Physical Society, 2021
2021
Generalized ORGaNICs: Towards a Unifying Framework for Neural Dynamics
S Rawat, D Heeger, S Martiniani
Bulletin of the American Physical Society, 2021
2021
High-Throughput Developability Assays Enable Library-Scale Identification of Producible Protein Scaffold Variants
AW Golinski, KM Mischler, S Laxminarayan, N Neurock, M Fossing, ...
bioRxiv, 422755, 2020
2020
On the complexity of energy landscapes: algorithms and a direct test of the Edwards conjecture
S Martiniani
University of Cambridge, 2017
2017
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Articles 1–17