| Predicting chemical shifts with graph neural networks Z Yang, M Chakraborty, AD White Chemical science 12 (32), 10802-10809, 2021 | 47 | 2021 |
| Graph neural network based coarse-grained mapping prediction Z Li, GP Wellawatte, M Chakraborty, HA Gandhi, C Xu, AD White Chemical science 11 (35), 9524-9531, 2020 | 45 | 2020 |
| Encoding and selecting coarse-grain mapping operators with hierarchical graphs M Chakraborty, C Xu, AD White The Journal of Chemical Physics 149 (13), 134106, 2018 | 43 | 2018 |
| Is Preservation of Symmetry Necessary for Coarse-Graining? M Chakraborty, J Xu, AD White Physical Chemistry Chemical Physics, 2020 | 22 | 2020 |
| Experimentally Consistent Simulation of Aβ21–30 Peptides with a Minimal NMR Bias DB Amirkulova, M Chakraborty, AD White The Journal of Physical Chemistry B 124 (38), 8266-8277, 2020 | 5 | 2020 |
| Hoomd-tf: Gpu-accelerated, online machine learning in the hoomd-blue molecular dynamics engine R Barrett, M Chakraborty, D Amirkulova, H Gandhi, G Wellawatte, A White Journal of Open Source Software 5 (51), 2020 | 5 | 2020 |
| Infrared irradiation aided fabrication of Mn impregnated-natural bone adsorbent: Efficacy evaluation in aqueous Cr (VI) removal PM R. Chakraborty, M. Chakraborty, A. Mitra Journal of Water Process Engineering 6, 32–41, 2015 | 5 | 2015 |
| Reconstruction of the interatomic forces from dynamic scanning transmission electron microscopy data M Chakraborty, M Ziatdinov, O Dyck, S Jesse, AD White, SV Kalinin Journal of Applied Physics 127 (22), 2020 | 2 | 2020 |
| A GPU-accelerated machine learning framework for molecular simulation: Hoomd-blue with TensorFlow R Barrett, M Chakraborty, D Amirkulova, H Gandhi, A White | 2 | 2019 |
| Predicting chemical shifts with graph neural networks. Z Yang, M Chakraborty, AD White Acta Crystallographica Section A: Foundations of Crystallography 79, a38-a38, 2022 | | 2022 |
| Correction: Graph neural network based coarse-grained mapping prediction Z Li, GP Wellawatte, M Chakraborty, HA Gandhi, C Xu, AD White Chemical Science 12 (35), 11922-11922, 2021 | | 2021 |
| Experimentally Consistent Simulation of Aβ₂₁–₃₀ Peptides with a Minimal NMR Bias DB Amirkulova, M Chakraborty, AD White | | 2020 |
| Studying Multiscale Phenomena with Simulation and Experiments M Chakraborty University of Rochester, 2020 | | 2020 |
| Studying the Importance of Preserving Symmetry in Coarse-Grained Alkanes M Chakraborty, A White 2019 AIChE Annual Meeting, 2019 | | 2019 |
| The Use of Experiment Directed Simulations to Improve the Accuracy of Simulations D Amirkulova, M Chakraborty 2019 AIChE Annual Meeting, 2019 | | 2019 |
| Effects of Coexisting Familial Mutants on Wild Type Amyloidβ21-30 Assembly M Chakraborty, H Gandhi, D Amirkulova, A White 2019 AIChE Annual Meeting, 2019 | | 2019 |
| Systematic Coarse-Grained Mapping and Potential Learning M Chakraborty, A White 2019 AIChE Annual Meeting, 2019 | | 2019 |
| HOOMD-TF: Online Machine Learning in Molecular Dynamics Simulations R Barrett, M Chakraborty, D Amirkulova, H Gandhi, A White 2019 AIChE Annual Meeting, 2019 | | 2019 |
| Structural and dynamic properties of A beta 21-30 with experiments and simulations D Amirkulova, M Chakraborty, A White ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 258, 2019 | | 2019 |
| Implementation and Automation of a Hierarchical Graph Based Approach for Extracting Coarse-Grain Mapping Operators M Chakraborty, A White 2018 AIChE Annual Meeting, 2018 | | 2018 |
Andrew D. WhiteUniversity of RochesterVerifierad e-postadress på rochester.edu
