Luigi Sbailò

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All published works

Action	Title	Year	Authors
+ PDF Chat	Roadmap on data-centric materials science	2024	Sebastian Bauer Peter Benner Tristan Bereau Volker Blüm Mario Boley Christian Carbogno C. Richard A. Catlow Gerhard Dehm Sebastian Eibl Ralph Ernstorfer
+	Roadmap on Data-Centric Materials Science	2024	Matthias Scheffler Sebastian Bauer Peter Benner Tristan Bereau Volker Blüm Mario Boley Christian Carbogno C. Richard A. Catlow Gerhard Dehm Sebastian Eibl
+	Roadmap on Data-Centric Materials Science	2024	Matthias Scheffler Sebastian Bauer Peter Benner Tristan Bereau Volker Blüm Mario Boley Christian Carbogno C. Richard A. Catlow Gerhard Dehm Sebastian Eibl
+	Roadmap on Data-Centric Materials Science	2024	Matthias Scheffler Sebastian Bauer Peter Benner Tristan Bereau Volker Blüm Mario Boley Christian Carbogno C. Richard A. Catlow Gerhard Dehm Sebastian Eibl
+ PDF Chat	Roadmap on Data-Centric Materials Science	2024	Sebastian Bauer Peter Benner Tristan Bereau Volker Blüm Mario Boley Christian Carbogno C. Richard A. Catlow Gerhard Dehm Sebastian Eibl Ralph Ernstorfer
+	Uncertainty Quantification in Deep Neural Networks through Statistical Inference on Latent Space	2023	Luigi Sbailò Luca M. Ghiringhelli
+	Emergence of Latent Binary Encoding in Deep Neural Network Classifiers	2023	Luigi Sbailò Luca M. Ghiringhelli
+	The NOMAD Artificial-Intelligence Toolkit: Turning materials-science data into knowledge and understanding	2022	Luigi Sbailò Ádám Fekete Luca M. Ghiringhelli Matthias Scheffler
+ PDF Chat	Neural mode jump Monte Carlo	2021	Luigi Sbailò Manuel Dibak Frank Noé
+	Neural Mode Jump Monte Carlo	2019	Luigi Sbailò Manuel Dibak Frank Noé
+ PDF Chat	On the formalization of asynchronous first passage algorithms	2019	Luigi Sbailò Luigi Delle Site
+	Neural Mode Jump Monte Carlo	2019	Luigi Sbailò Manuel Dibak Frank Noé
+ PDF Chat	An efficient multi-scale Green’s function reaction dynamics scheme	2017	Luigi Sbailò Frank Noé

Common Coauthors

Coauthor	Papers Together
Luca M. Ghiringhelli	8
Matthias Scheffler	6
Tristan Bereau	5
Sebastian Kokott	5
Jörg Neugebauer	5
Annette Trunschke	5
Ulf Saalmann	5
Jaber Rezaei Mianroodi	5
Ádám Fekete	5
Ye Wei	5
Thomas Kosch	5
Christian H. Liebscher	5
Peter Fratzl	5
Jan M. Rost	5
Thomas A. R. Purcell	5
F. Merz	5
Sebastian Bauer	5
Andreas Marek	5
Marcel Schloz	5
Lara Kabalan	5
Dierk Raabe	5
C. Richard A. Catlow	5
Phuc Luong	5
Daniel F. Schmidt	5
Ralph Ernstorfer	5
Mario Boley	5
Volker Blüm	5
Anton Gladyshev	5
Zhongwei Lu	5
Christoph T. Koch	5
Alaukik Saxena	5
Igor Kowalec	5
Baptiste Gault	5
Simon Teshuva	5
Markus Rampp	5
Gerhard Weikum	5
Andreas Leitherer	5
Mariana Rossi	5
Mohammad S. Khorrami	5
Meng Zhao	5
Christian Carbogno	5
Sebastian Eibl	5
Peter Benner	5
Yiyu Yao	5
Andrew J. Logsdail	5
Lucas Foppa	5
Markus Scheidgen	5
R. Patrick Xian	5
Petr Karpov	5
Sajal Kumar Giri	5

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Multi-fidelity cost-aware Bayesian optimization	2023	Zahra Zanjani Foumani Mehdi Shishehbor Amin Yousefpour Ramin Bostanabad	4
+ PDF Chat	Deep reinforcement learning for data-driven adaptive scanning in ptychography	2023	Marcel Schloz Johannes Müller Thomas C. Pekin Wouter Van den Broek Jacob Madsen Toma Susi Christoph T. Koch	4
+ PDF Chat	Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns	2022	Joydeep Munshi Alexander Rakowski Benjamin H. Savitzky Steven E. Zeltmann Jim Ciston Matthew Henderson Shreyas Cholia Andrew M. Minor Maria K. Y. Chan Colin Ophus	4
+ PDF Chat	The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts	2023	Richard Tran Janice Lan Muhammed Shuaibi Brandon M. Wood Siddharth Goyal Abhishek Das Javier Heras‐Domingo Adeesh Kolluru Ammar Rizvi Nima Shoghi	4
+ PDF Chat	A Roadmap for Edge Computing Enabled Automated Multidimensional Transmission Electron Microscopy	2022	Debangshu Mukherjee Kevin Roccapriore Anees Al‐Najjar Ayana Ghosh Jacob Hinkle Andrew R. Lupini Rama K. Vasudevan Sergei V. Kalinin Olga S. Ovchinnikova Maxim Ziatdinov	4
+	Understanding and Modeling Polymers: The Challenge of Multiple Scales	2022	Friederike Schmid	4
+ PDF Chat	Artificial-intelligence-driven discovery of catalyst genes with application to CO2 activation on semiconductor oxides	2022	Aliaksei Mazheika Yang‐Gang Wang Rosendo Valero Francesc Viñes Francesc Illas Luca M. Ghiringhelli Sergey V. Levchenko Matthias Scheffler	4
+ PDF Chat	Machine learning–enabled high-entropy alloy discovery	2022	Ziyuan Rao Po‐Yen Tung Ruiwen Xie Ye Wei Hongbin Zhang Alberto Ferrari T.P.C. Klaver Fritz Körmann T.S. Prithiv Alisson Kwiatkowski da Silva	4
+	Near-real-time diagnosis of electron optical phase aberrations in scanning transmission electron microscopy using an artificial neural network	2022	Giovanni Bertoni Enzo Rotunno Daan Marsmans Peter Tiemeijer Amir H. Tavabi Rafal E. Dunin‐Borkowski Vincenzo Grillo	4
+ PDF Chat	Phase Object Reconstruction for 4D-STEM using Deep Learning	2023	Thomas Friedrich Chu-Ping Yu Johan Verbeeck Sandra Van Aert	4
+ PDF Chat	Absorbers as detectors for unbound quantum systems	2022	Sølve Selstø	4
+ PDF Chat	Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery	2021	Lucas Foppa Luca M. Ghiringhelli	4
+ PDF Chat	OPTIMADE, an API for exchanging materials data	2021	Casper Welzel Andersen Rickard Armiento Evgeny Blokhin G. J. Conduit Shyam Dwaraknath Matthew L. Evans Ádám Fekete Abhijith Gopakumar S. Gražulis Andrius Merkys	4
+ PDF Chat	Learning the stress-strain fields in digital composites using Fourier neural operator	2022	Meer Mehran Rashid Tanu Pittie Souvik Chakraborty N. M. Anoop Krishnan	4
+	Free, flexible and fast: Orientation mapping using the multi-core and GPU-accelerated template matching capabilities in the Python-based open source 4D-STEM analysis toolbox Pyxem	2022	Niels Cautaerts Phillip Crout Håkon Wiik Ånes Éric Prestat Jiwon Jeong Gerhard Dehm Christian H. Liebscher	4
+	Physics-Informed Neural Operator for Learning Partial Differential Equations	2021	Zongyi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar	4
+	Greed Is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation	2021	George De Ath Richard Everson Alma Rahat Jonathan E. Fieldsend	4
+ PDF Chat	Quality of uncertainty estimates from neural network potential ensembles	2022	Leonid Kahle Federico Zipoli	4
+ PDF Chat	<i>Ab initio</i> machine learning of phase space averages	2022	Jan Weinreich Dominik Lemm Guido Falk von Rudorff O. Anatole von Lilienfeld	4
+ PDF Chat	Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm	2020	Alexander Dunn Qi Wang Alex M. Ganose Daniel Dopp Anubhav Jain	4
+	Neural Spatio-Temporal Point Processes	2020	Ricky T. Q. Chen Brandon Amos Maximilian Nickel	4
+ PDF Chat	A machine learning route between band mapping and band structure	2022	R. Patrick Xian Vincent Stimper Marios Zacharias Maciej Dendzik Shuo Dong Samuel Beaulieu Bernhard Schölkopf Martin Wolf Laurenz Rettig Christian Carbogno	4
+ PDF Chat	On-the-fly closed-loop materials discovery via Bayesian active learning	2020	A. Gilad Kusne Heshan Yu Changming Wu Huairuo Zhang Jason Hattrick‐Simpers Brian DeCost Suchismita Sarker Corey Oses Cormac Toher Stefano Curtarolo	4
+ PDF Chat	Optimizations of the eigensolvers in the ELPA library	2019	Pavel Kůs Andreas Marek S. Kocher Hagen-Henrik Kowalski Christian Carbogno Ch. Scheurer Karsten Reuter Matthias Scheffler Hermann Lederer	4
+ PDF Chat	Perspectives for analyzing non-linear photo-ionization spectra with deep neural networks trained with synthetic Hamilton matrices	2020	Sajal Kumar Giri Lázaro Alonso Ulf Saalmann Jan M. Rost	4
+ PDF Chat	Convolutional neural network-assisted recognition of nanoscale L12 ordered structures in face-centred cubic alloys	2021	Yue Li Xuyang Zhou Timoteo Colnaghi Ye Wei Andreas Marek Hongxiang Li Stefan Bauer Markus Rampp Leigh T. Stephenson	4
+ PDF Chat	Machine-learning-enhanced time-of-flight mass spectrometry analysis	2021	Ye Wei Rama Srinivas Varanasi Torsten Schwarz Leonie Gomell Huan Zhao David J. Larson Binhan Sun Geng Liu Hao Chen Dierk Raabe	4
+	Non-parametric Jensen-Shannon Divergence	2015	Hoang Vu Nguyen Jilles Vreeken	4
+ PDF Chat	Physics-Inspired Structural Representations for Molecules and Materials	2021	Félix Musil Andrea Grisafi Albert P. Bartók Christoph Ortner Gábor Cśanyi Michele Ceriotti	4
+ PDF Chat	On strong-scaling and open-source tools for analyzing atom probe tomography data	2021	Markus Kühbach Priyanshu Bajaj Huan Zhao Murat Han Celik Eric A. Jägle Baptiste Gault	4
+ PDF Chat	NOMAD: The FAIR concept for big data-driven materials science	2018	Claudia Draxl Matthias Scheffler	4
+ PDF Chat	Uncertainty Quantification Using Neural Networks for Molecular Property Prediction	2020	Lior Hirschfeld Kyle Swanson Kevin Yang Regina Barzilay Connor W. Coley	4
+ PDF Chat	Uncovering structure-property relationships of materials by subgroup discovery	2017	Bryan R. Goldsmith Mario Boley Jilles Vreeken Matthias Scheffler Luca M. Ghiringhelli	4
+ PDF Chat	Purifying Electron Spectra from Noisy Pulses with Machine Learning Using Synthetic Hamilton Matrices	2020	Sajal Kumar Giri Ulf Saalmann Jan M. Rost	4
+ PDF Chat	Crowd-sourcing materials-science challenges with the NOMAD 2018 Kaggle competition	2019	Christopher Sutton Luca M. Ghiringhelli T. Yamamoto Yury Lysogorskiy Lars Blumenthal Thomas Hammerschmidt Jacek Gołębiowski Xiang‐Yue Liu Angelo Ziletti Matthias Scheffler	4
+ PDF Chat	Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations	2017	Maxim Ziatdinov Ondrej Dyck Artem Maksov Xufan Li Xiahan Sang Kai Xiao Raymond R. Unocic Rama K. Vasudevan Stephen Jesse Sergei V. Kalinin	4
+ PDF Chat	FAIR data enabling new horizons for materials research	2022	Matthias Scheffler Martin Aeschlimann M. Albrecht Tristan Bereau Hans–Joachim Bungartz Claudia Felser Mark Greiner Axel Groß Christoph T. Koch Kurt Kremer	4
+	GPU-acceleration of the ELPA2 distributed eigensolver for dense symmetric and hermitian eigenproblems	2020	Victor Wen‐zhe Yu Jonathan E. Moussa Pavel Kůs Andreas Marek Peter Messmer Mina Yoon Hermann Lederer Volker Blüm	4
+ PDF Chat	Open Catalyst 2020 (OC20) Dataset and Community Challenges	2021	Lowik Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi Morgane Rivière Kevin Tran Javier Heras‐Domingo Caleb Ho Weihua Hu	4
+ PDF Chat	Fast and Accurate Uncertainty Estimation in Chemical Machine Learning	2019	Félix Musil Michael J. Willatt Mikhail Langovoy Michele Ceriotti	4
+	Machine Learning of Coarse-Grained Molecular Dynamics Force Fields	2019	Jiang Wang Simon Olsson Christoph Wehmeyer Adrià Pérez Nicholas E. Charron Gianni De Fabritiis Frank Noé Cecilia Clementi	4
+	AiiDAlab – an ecosystem for developing, executing, and sharing scientific workflows	2020	Aliaksandr V. Yakutovich Kristjan Eimre Ole Schütt Leopold Talirz Carl S. Adorf Casper Welzel Andersen Edward Ditler Dou Du Daniele Passerone Berend Smit	4
+	Drug–Membrane Permeability across Chemical Space	2019	Roberto Menichetti Kiran H. Kanekal Tristan Bereau	4
+	One-hundred-three compound band-structure benchmark of post-self-consistent spin-orbit coupling treatments in density functional theory	2017	William Huhn Volker Blüm	4
+ PDF Chat	On-the-fly machine learning force field generation: Application to melting points	2019	Ryosuke Jinnouchi Ferenc Karsai Georg Kresse	4
+ PDF Chat	Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons	2010	Albert P. Bartók M. C. Payne Risi Kondor Gábor Cśanyi	4
+ PDF Chat	Bootstrap Methods: Another Look at the Jackknife	1979	B. Efron	4
+ PDF Chat	AiiDA: automated interactive infrastructure and database for computational science	2015	Giovanni Pizzi Andrea Cepellotti Riccardo Sabatini Nicola Marzari Boris Kozinsky	4
+ PDF Chat	AFLOW: An automatic framework for high-throughput materials discovery	2012	Stefano Curtarolo Wahyu Setyawan Gus L. W. Hart Michal Jahnátek Roman V. Chepulskii Richard H. Taylor Shidong Wang Junkai Xue Kesong Yang Ohad Levy	4
+	On the Design Fundamentals of Diffusion Models: A Survey	2023	Ziyi Chang George Alex Koulieris Hubert P. H. Shum	4