default search action
Olexandr Isayev
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j14]Kenneth M. Merz Jr.
, Yee-Siew Choong
Editorial: Machine Learning in Materials Science. J. Chem. Inf. Model. 64(10): 3959-3960 (2024) - [c2]Jiayuan Chen
Uncertainty-Aware Yield Prediction with Multimodal Molecular Features. AAAI 2024: 8274-8282 - [c1]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang:
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. ICLR 2024 - 2023
- [j13]Filipp Gusev
Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling. J. Chem. Inf. Model. 63(2): 583-594 (2023) - [i8]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. CoRR abs/2310.00115 (2023) - [i7]Pavlo O. Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Olexandr Isayev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Jr, Yuming Su
MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows. CoRR abs/2310.20155 (2023) - 2022
- [j12]Hatice Gokcan
Simulations of Pathogenic E1α Variants: Allostery and Impact on Pyruvate Dehydrogenase Complex-E1 Structure and Function. J. Chem. Inf. Model. 62(14): 3463-3475 (2022) - [j11]Zhen Liu
Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials. J. Chem. Inf. Model. 62(22): 5373-5382 (2022) - [j10]Mohit Pandey
The transformational role of GPU computing and deep learning in drug discovery. Nat. Mach. Intell. 4(3): 211-221 (2022) - 2021
- [j9]Marco Fronzi
Active Learning in Bayesian Neural Networks for Bandgap Predictions of Novel Van der Waals Heterostructures. Adv. Intell. Syst. 3(11): 2100080 (2021) - [j8]Farshad Firouzi
Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World. IEEE Internet Things J. 8(16): 12826-12846 (2021) - [j7]Maria Korshunova
OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design. J. Chem. Inf. Model. 61(1): 7-13 (2021) - [i6]Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob H. Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer:
Simulation Intelligence: Towards a New Generation of Scientific Methods. CoRR abs/2112.03235 (2021) - 2020
- [j6]Xiang Gao
TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials. J. Chem. Inf. Model. 60(7): 3408-3415 (2020)
2010 – 2019
- 2019
- [j5]Sherif Farag
Inter-Modular Linkers play a crucial role in governing the biosynthesis of non-ribosomal peptides. Bioinform. 35(19): 3584-3591 (2019) - [j4]Michael Fernández
Quantitative Structure-Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects. J. Chem. Inf. Model. 59(4): 1306-1313 (2019) - [i5]Mariya Popova, Mykhailo Shvets, Junier Oliva, Olexandr Isayev:
MolecularRNN: Generating realistic molecular graphs with optimized properties. CoRR abs/1905.13372 (2019) - [i4]Marco Fronzi
Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery. CoRR abs/1911.11559 (2019) - 2018
- [i3]Justin S. Smith, Ben Nebgen, Nicholas Lubbers, Olexandr Isayev, Adrian E. Roitberg:
Less is more: sampling chemical space with active learning. CoRR abs/1801.09319 (2018) - 2017
- [i2]Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg:
ANI-1: A data set of 20M off-equilibrium DFT calculations for organic molecules. CoRR abs/1708.04987 (2017) - [i1]Mariya Popova, Olexandr Isayev, Alexander Tropsha:
Deep Reinforcement Learning for De-Novo Drug Design. CoRR abs/1711.10907 (2017) - 2015
- [j3]Liudmyla K. Sviatenko
Are the reduction and oxidation properties of nitrocompounds dissolved in water different from those produced when adsorbed on a silica surface? A DFT M05-2X computational study. J. Comput. Chem. 36(14): 1029-1035 (2015) - 2011
- [j2]Liudmyla K. Sviatenko
Toward robust computational electrochemical predicting the environmental fate of organic pollutants. J. Comput. Chem. 32(10): 2195-2203 (2011)
2000 – 2009
- 2007
- [j1]Olexandr Isayev
Theoretical calculations: Can Gibbs free energy for intermolecular complexes be predicted efficiently and accurately? J. Comput. Chem. 28(9): 1598-1609 (2007)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-05 22:02 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: