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Gihan Panapitiya

Showing results (1-10 of 10) with videos related to

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Journal of Chemical Information and Modeling|May 13, 2025
Extracting Material Property Measurements from Scientific Literature with Limited AnnotationsJessica Kong, Gihan Panapitiya, Emily Saldanha
Scientific Reports|June 25, 2026
AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentationGihan Panapitiya, Emily Saldanha, Heather Job, et al.
RSC Advances|January 26, 2026
Out-of-distribution evaluation of active learning pipelines for molecular property predictionTianzhixi Yin, Peiyuan Gao, Gihan Panapitiya, et al.
Journal of the American Chemical Society|February 25, 2026
FragNet: A Graph Neural Network for Molecular Property Prediction with Four Levels of InterpretabilityGihan Panapitiya, Peiyuan Gao, C Mark Maupin, et al.
Journal of Cheminformatics|November 8, 2023
Evaluating uncertainty-based active learning for accelerating the generalization of molecular property predictionTianzhixi Yin, Gihan Panapitiya, Elizabeth D Coda, et al.
Physical Chemistry Chemical Physics : PCCP|May 16, 2018
Structural and catalytic properties of the Au<sub>25-x</sub>Ag<sub>x</sub>(SCH<sub>3</sub>)<sub>18</sub> (x = 6, 7, 8) nanoclusterGihan Panapitiya, Hong Wang, Yuxiang Chen, et al.
ACS Omega|May 16, 2022
Evaluation of Deep Learning Architectures for Aqueous Solubility PredictionGihan Panapitiya, Michael Girard, Aaron Hollas, et al.
Journal of the American Chemical Society|November 9, 2018
Machine-Learning Prediction of CO Adsorption in Thiolated, Ag-Alloyed Au NanoclustersGihan Panapitiya, Guillermo Avendaño-Franco, Pengju Ren, et al.
The Journal of Physical Chemistry Letters|April 5, 2016
Slow Relaxation of Surface Plasmon Excitations in Au55: The Key to Efficient Plasmonic Heating in Au/TiO2Oshadha Ranasingha, Hong Wang, Vladimír Zobač, et al.
Nanoscale|November 30, 2017
Controlling Ag-doping in [Ag<sub>x</sub>Au<sub>25-x</sub>(SC<sub>6</sub>H<sub>11</sub>)<sub>18</sub>]<sup>-</sup> nanoclusters: cryogenic optical, electronic and electrocatalytic propertiesRenxi Jin, Shuo Zhao, Chong Liu, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Journal of Chemical Information and Modeling|May 13, 2025
Extracting Material Property Measurements from Scientific Literature with Limited AnnotationsJessica Kong, Gihan Panapitiya, Emily Saldanha
Scientific Reports|June 25, 2026
AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentationGihan Panapitiya, Emily Saldanha, Heather Job, et al.
RSC Advances|January 26, 2026
Out-of-distribution evaluation of active learning pipelines for molecular property predictionTianzhixi Yin, Peiyuan Gao, Gihan Panapitiya, et al.
Journal of the American Chemical Society|February 25, 2026
FragNet: A Graph Neural Network for Molecular Property Prediction with Four Levels of InterpretabilityGihan Panapitiya, Peiyuan Gao, C Mark Maupin, et al.
Journal of Cheminformatics|November 8, 2023
Evaluating uncertainty-based active learning for accelerating the generalization of molecular property predictionTianzhixi Yin, Gihan Panapitiya, Elizabeth D Coda, et al.
Physical Chemistry Chemical Physics : PCCP|May 16, 2018
Structural and catalytic properties of the Au<sub>25-x</sub>Ag<sub>x</sub>(SCH<sub>3</sub>)<sub>18</sub> (x = 6, 7, 8) nanoclusterGihan Panapitiya, Hong Wang, Yuxiang Chen, et al.
ACS Omega|May 16, 2022
Evaluation of Deep Learning Architectures for Aqueous Solubility PredictionGihan Panapitiya, Michael Girard, Aaron Hollas, et al.
Journal of the American Chemical Society|November 9, 2018
Machine-Learning Prediction of CO Adsorption in Thiolated, Ag-Alloyed Au NanoclustersGihan Panapitiya, Guillermo Avendaño-Franco, Pengju Ren, et al.
The Journal of Physical Chemistry Letters|April 5, 2016
Slow Relaxation of Surface Plasmon Excitations in Au55: The Key to Efficient Plasmonic Heating in Au/TiO2Oshadha Ranasingha, Hong Wang, Vladimír Zobač, et al.
Nanoscale|November 30, 2017
Controlling Ag-doping in [Ag<sub>x</sub>Au<sub>25-x</sub>(SC<sub>6</sub>H<sub>11</sub>)<sub>18</sub>]<sup>-</sup> nanoclusters: cryogenic optical, electronic and electrocatalytic propertiesRenxi Jin, Shuo Zhao, Chong Liu, et al.
Pageof 1