Audacity of huge: overcoming challenges of data scarcity and data
quality for machine learning in computational materials discovery

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery

2 November 2021

Heather J. Kulik

Papers citing "Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery"

13 / 13 papers shown

Title
MOFSimplify: Machine Learning Models with Extracted Stability Data of Three Thousand Metal-Organic Frameworks Aditya Nandy Gianmarco G. Terrones N. Arunachalam Chenru Duan D. Kastner Heather J. Kulik AI4CE 45 29 0 16 Sep 2021
Deciphering Cryptic Behavior in Bimetallic Transition Metal Complexes with Machine Learning Michael G. Taylor Aditya Nandy Connie C. Lu Heather J. Kulik 34 8 0 29 Jul 2021
Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks Aditya Nandy Chenru Duan Heather J. Kulik AI4CE 39 118 0 24 Jun 2021
Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles Chenru Duan Shuxin Chen Michael G. Taylor Fan Liu Heather J. Kulik AI4CE 42 18 0 24 Jun 2021
Learning the exchange-correlation functional from nature with fully differentiable density functional theory M. F. Kasim S. Vinko 119 67 0 08 Feb 2021
A Two-stage Framework for Compound Figure Separation Weixin Jiang Eric S. Schwenker Trevor Spreadbury N. Ferrier Maria K. Y. Chan O. Cossairt 23 10 0 25 Jan 2021
Quantum deep field: data-driven wave function, electron density generation, and atomization energy prediction and extrapolation with machine learning Masashi Tsubaki T. Mizoguchi 45 37 0 16 Nov 2020
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics Li Li Stephan Hoyer Ryan Pederson Ruoxi Sun E. D. Cubuk Patrick F. Riley K. Burke AI4CE 58 122 0 17 Sep 2020
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning Kevin Maik Jablonka D. Ongari S. M. Moosavi B. Smit AI4CE 68 357 0 18 Jan 2020
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 202 455 0 16 Sep 2019
Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions Kristof T. Schütt M. Gastegger A. Tkatchenko K. Müller R. Maurer AI4CE 75 388 0 24 Jun 2019
Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks Edward J. Kim Z. Jensen Alexander van Grootel Kevin Huang Matthew Staib ... Haw-Shiuan Chang Emma Strubell Andrew McCallum Stefanie Jegelka E. Olivetti 64 115 0 31 Dec 2018
By-passing the Kohn-Sham equations with machine learning Felix Brockherde Leslie Vogt Li Li M. Tuckerman K. Burke K. Müller AI4CE 64 606 0 09 Sep 2016

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.