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All published works
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Title
Year
Authors
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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
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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
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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
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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
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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
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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
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PDF
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Building Nonparametric n-Body Force Fields Using Gaussian Process Regression
2020
Aldo Glielmo
Claudio Zeni
Ádám Fekete
Alessandro De Vita
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PDF
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Building machine learning force fields for nanoclusters
2018
Claudio Zeni
Kevin Rossi
Aldo Glielmo
Ádám Fekete
Nicola Gaston
Francesca Baletto
Alessandro De Vita
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Imeall: A computational framework for the calculation of the atomistic properties of grain boundaries
2018
Henry Lambert
Ádám Fekete
James R. Kermode
Alessandro De Vita
Common Coauthors
Coauthor
Papers Together
Thomas A. R. Purcell
6
Markus Scheidgen
6
Matthias Scheffler
6
Markus Rampp
5
Simon Teshuva
5
Pawan Goyal
5
Igor Kowalec
5
Sebastian Eibl
5
Andrew J. Logsdail
5
Ye Wei
5
Jason Hattrick‐Simpers
5
Sajal Kumar Giri
5
Kurt Kremer
5
Gerhard Dehm
5
Mario Boley
5
F. Merz
5
Christian Carbogno
5
Ulf Saalmann
5
Jaber Rezaei Mianroodi
5
Yiyu Yao
5
Dierk Raabe
5
Lucas Foppa
5
R. Patrick Xian
5
Christoph T. Koch
5
Petr Karpov
5
Peter Fratzl
5
Jörg Neugebauer
5
Christoph Freysoldt
5
Annette Trunschke
5
Jan M. Rost
5
Meng Zhao
5
Volker Blüm
5
Sebastian Bauer
5
Andreas Marek
5
Tristan Bereau
5
Anton Gladyshev
5
Marcel Schloz
5
Lara Kabalan
5
Alaukik Saxena
5
Peter Benner
5
Sebastian Kokott
5
Luigi Sbailò
5
Baptiste Gault
5
C. Richard A. Catlow
5
Phuc Luong
5
Thomas Kosch
5
Christian H. Liebscher
5
Daniel F. Schmidt
5
Ralph Ernstorfer
5
Gerhard Weikum
5
Commonly Cited References
Action
Title
Year
Authors
# of times referenced
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PDF
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Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons
2010
Albert P. Bartók
M. C. Payne
Risi Kondor
Gábor Cśanyi
7
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PDF
Chat
AiiDA: automated interactive infrastructure and database for computational science
2015
Giovanni Pizzi
Andrea Cepellotti
Riccardo Sabatini
Nicola Marzari
Boris Kozinsky
5
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PDF
Chat
NOMAD: The FAIR concept for big data-driven materials science
2018
Claudia Draxl
Matthias Scheffler
5
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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
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
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Understanding and Modeling Polymers: The Challenge of Multiple Scales
2022
Friederike Schmid
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
+
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
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
+
PDF
Chat
Phase Object Reconstruction for 4D-STEM using Deep Learning
2023
Thomas Friedrich
Chu-Ping Yu
Johan Verbeeck
Sandra Van Aert
4
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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
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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
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PDF
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<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
Quality of uncertainty estimates from neural network potential ensembles
2022
Leonid Kahle
Federico Zipoli
4
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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
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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
+
Neural Spatio-Temporal Point Processes
2020
Ricky T. Q. Chen
Brandon Amos
Maximilian Nickel
4
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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
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
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
+
Drug–Membrane Permeability across Chemical Space
2019
Roberto Menichetti
Kiran H. Kanekal
Tristan Bereau
4
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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
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PDF
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Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery
2021
Lucas Foppa
Luca M. Ghiringhelli
4
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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
Uncovering structure-property relationships of materials by subgroup discovery
2017
Bryan R. Goldsmith
Mario Boley
Jilles Vreeken
Matthias Scheffler
Luca M. Ghiringhelli
4
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PDF
Chat
Bootstrap Methods: Another Look at the Jackknife
1979
B. Efron
4
+
PDF
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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
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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
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PDF
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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
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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
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Purifying Electron Spectra from Noisy Pulses with Machine Learning Using Synthetic Hamilton Matrices
2020
Sajal Kumar Giri
Ulf Saalmann
Jan M. Rost
4
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Greed Is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation
2021
George De Ath
Richard Everson
Alma Rahat
Jonathan E. Fieldsend
4
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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
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PDF
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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
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PDF
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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
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Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
2020
Lior Hirschfeld
Kyle Swanson
Kevin Yang
Regina Barzilay
Connor W. Coley
4
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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
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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
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Non-parametric Jensen-Shannon Divergence
2015
Hoang Vu Nguyen
Jilles Vreeken
4
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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
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Fast and Accurate Uncertainty Estimation in Chemical Machine Learning
2019
Félix Musil
Michael J. Willatt
Mikhail Langovoy
Michele Ceriotti
4
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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
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Absorbers as detectors for unbound quantum systems
2022
Sølve Selstø
4
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On-the-fly machine learning force field generation: Application to melting points
2019
Ryosuke Jinnouchi
Ferenc Karsai
Georg Kresse
4
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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
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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
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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
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Physics-Inspired Structural Representations for Molecules and Materials
2021
Félix Musil
Andrea Grisafi
Albert P. Bartók
Christoph Ortner
Gábor Cśanyi
Michele Ceriotti
4
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Multi-fidelity cost-aware Bayesian optimization
2023
Zahra Zanjani Foumani
Mehdi Shishehbor
Amin Yousefpour
Ramin Bostanabad
4
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On the Design Fundamentals of Diffusion Models: A Survey
2023
Ziyi Chang
George Alex Koulieris
Hubert P. H. Shum
4