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Journal of Chemical Theory and Computation|June 16, 2020
Data-Driven Approaches Can Overcome the Cost-Accuracy Trade-Off in Multireference DiagnosticsChenru Duan, Fang Liu, Aditya Nandy, et al.
The Journal of Physical Chemistry Letters|May 11, 2021
Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials DiscoveryChenru Duan, Fang Liu, Aditya Nandy, et al.
The Journal of Physical Chemistry Letters|July 22, 2020
Semi-supervised Machine Learning Enables the Robust Detection of Multireference Character at Low CostChenru Duan, Fang Liu, Aditya Nandy, et al.
Journal of the American Chemical Society|October 13, 2021
Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic FrameworksAditya Nandy, Chenru Duan, Heather J Kulik
Annual Review of Chemical and Biomolecular Engineering|March 23, 2022
Machine Learning for the Discovery, Design, and Engineering of MaterialsChenru Duan, Aditya Nandy, Heather J Kulik
Accounts of Chemical Research|January 22, 2021
Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles DesignJon Paul Janet, Chenru Duan, Aditya Nandy, et al.
Journal of Chemical Theory and Computation|March 13, 2019
Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning ModelsChenru Duan, Jon Paul Janet, Fang Liu, et al.
Physical Chemistry Chemical Physics : PCCP|March 6, 2023
Insights into the deviation from piecewise linearity in transition metal complexes from supervised machine learning modelsYael Cytter, Aditya Nandy, Chenru Duan, et al.
Journal of Chemical Theory and Computation|December 22, 2022
DFT-Based Multireference Diagnostics in the Solid State: Application to Metal-Organic FrameworksYeongsu Cho, Aditya Nandy, Chenru Duan, et al.
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