Ádám Fekete

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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
+ 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
+ PDF Chat Building Nonparametric n-Body Force Fields Using Gaussian Process Regression 2020 Aldo Glielmo
Claudio Zeni
Ádám Fekete
Alessandro De Vita
+ PDF Chat Building machine learning force fields for nanoclusters 2018 Claudio Zeni
Kevin Rossi
Aldo Glielmo
Ádám Fekete
Nicola Gaston
Francesca Baletto
Alessandro De Vita
+ 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
Commonly Cited References
Action Title Year Authors # of times referenced
+ PDF Chat Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons 2010 Albert P. Bartók
M. C. Payne
Risi Kondor
Gábor Cśanyi
7
+ PDF Chat AiiDA: automated interactive infrastructure and database for computational science 2015 Giovanni Pizzi
Andrea Cepellotti
Riccardo Sabatini
Nicola Marzari
Boris Kozinsky
5
+ PDF Chat NOMAD: The FAIR concept for big data-driven materials science 2018 Claudia Draxl
Matthias Scheffler
5
+ 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
+ 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
+ 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
+ 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
+ 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 Quality of uncertainty estimates from neural network potential ensembles 2022 Leonid Kahle
Federico Zipoli
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 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
+ 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
+ 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
+ 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 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 Bootstrap Methods: Another Look at the Jackknife 1979 B. Efron
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
+ 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
+ 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 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
+ 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
+ Greed Is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation 2021 George De Ath
Richard Everson
Alma Rahat
Jonathan E. Fieldsend
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 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 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 Uncertainty Quantification Using Neural Networks for Molecular Property Prediction 2020 Lior Hirschfeld
Kyle Swanson
Kevin Yang
Regina Barzilay
Connor W. Coley
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
+ 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
+ Non-parametric Jensen-Shannon Divergence 2015 Hoang Vu Nguyen
Jilles Vreeken
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
+ 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
+ PDF Chat Absorbers as detectors for unbound quantum systems 2022 Sølve Selstø
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 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 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 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 Multi-fidelity cost-aware Bayesian optimization 2023 Zahra Zanjani Foumani
Mehdi Shishehbor
Amin Yousefpour
Ramin Bostanabad
4
+ On the Design Fundamentals of Diffusion Models: A Survey 2023 Ziyi Chang
George Alex Koulieris
Hubert P. H. Shum
4