Heather J. Kulik

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 24

Top Topics

Chemical Reactions

Exploration Exploitation

Density Function

Top Venues

J. Comput. Chem.

J. Chem. Inf. Model.

Nat. Comput. Sci.

Publications

Chenru Duan, Guan-Horng Liu, Yuanqi Du, Tianrong Chen, Qiyuan Zhao, Haojun Jia, Carla P. Gomes, Evangelos A. Theodorou, Heather J. Kulik
React-OT: Optimal Transport for Generating Transition State in Chemical Reactions. CoRR (2024)
Freya Edholm, Aditya Nandy, Clorice R. Reinhardt, David W. Kastner, Heather J. Kulik
Protein3D: Enabling analysis and extraction of metal-containing sites from the Protein Data Bank with molSimplify. J. Comput. Chem. 45 (6) (2024)
Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J. Kulik
A transferable recommender approach for selecting the best density functional approximations in chemical discovery. Nat. Comput. Sci. 3 (1) (2023)
Chenru Duan, Yuanqi Du, Haojun Jia, Heather J. Kulik
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model. Nat. Comput. Sci. 3 (12) (2023)
Maria H. Rasmussen, Chenru Duan, Heather J. Kulik, Jan H. Jensen
Uncertain of uncertainties? A comparison of uncertainty quantification metrics for chemical data sets. J. Cheminformatics 15 (1) (2023)
Chenru Duan, Yuanqi Du, Haojun Jia, Heather J. Kulik
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model. CoRR (2023)
Gianmarco G. Terrones, Yu Chen, Archit Datar, Li-Chiang Lin, Heather J. Kulik, Yongchul G. Chung
SESAMI APP: An Accessible Interface for Surface Area Calculation of Materials from Adsorption Isotherms. J. Open Source Softw. 8 (87) (2023)
Chenru Duan, Aditya Nandy, Husain Adamji, Yuriy Roman-Leshkov, Heather J. Kulik
Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis. CoRR (2022)
Chenru Duan, Daniel B. K. Chu, Aditya Nandy, Heather J. Kulik
Two Wrongs Can Make a Right: A Transfer Learning Approach for Chemical Discovery with Chemical Accuracy. CoRR (2022)
Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J. Kulik
A Transferable Recommender Approach for Selecting the Best Density Functional Approximations in Chemical Discovery. CoRR (2022)
Gianmarco Terrones, Chenru Duan, Aditya Nandy, Heather J. Kulik
Low-cost machine learning approach to the prediction of transition metal phosphor excited state properties. CoRR (2022)
Chenru Duan, Adriana J. Ladera, Julian C.-L. Liu, Michael G. Taylor, Isuru R. Ariyarathna, Heather J. Kulik
Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character Across Known Transition Metal Complex Ligands. CoRR (2022)
Chenru Duan, Fang Liu, Aditya Nandy, Heather J. Kulik
Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery. CoRR (2022)
Aditya Nandy, Shuwen Yue, Changhwan Oh, Chenru Duan, Gianmarco G. Terrones, Yongchul G. Chung, Heather J. Kulik
A Database of Ultrastable MOFs Reassembled from Stable Fragments with Machine Learning Models. CoRR (2022)
Chenru Duan, Aditya Nandy, Gianmarco Terrones, David W. Kastner, Heather J. Kulik
Rapid Exploration of a 32.5M Compound Chemical Space with Active Learning to Discover Density Functional Approximation Insensitive and Synthetically Accessible Transitional Metal Chromophores. CoRR (2022)
Michael G. Taylor, Aditya Nandy, Connie C. Lu, Heather J. Kulik
Deciphering Cryptic Behavior in Bimetallic Transition Metal Complexes with Machine Learning. CoRR (2021)
Daniel R. Harper, Aditya Nandy, Naveen Arunachalam, Chenru Duan, Jon Paul Janet, Heather J. Kulik
Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery. CoRR (2021)
Aditya Nandy, G. Terrones, Naveen Arunachalam, C. Duan, D. W. Kastner, Heather J. Kulik
MOFSimplify: Machine Learning Models with Extracted Stability Data of Three Thousand Metal-Organic Frameworks. CoRR (2021)
Aditya Nandy, Chenru Duan, Heather J. Kulik
Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks. CoRR (2021)
Aditya Nandy, Chenru Duan, Heather J. Kulik
Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery. CoRR (2021)
Chenru Duan, Shuxin Chen, Michael G. Taylor, Fang Liu, Heather J. Kulik
Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles. CoRR (2021)
Helena W. Qi, Heather J. Kulik
Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis. J. Chem. Inf. Model. 59 (5) (2019)
Helena W. Qi, Heather J. Kulik
Reply to "Comment on 'Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis'". J. Chem. Inf. Model. 59 (9) (2019)
Efthymios I. Ioannidis, Terry Z. H. Gani, Heather J. Kulik
molSimplify: A toolkit for automating discovery in inorganic chemistry. J. Comput. Chem. 37 (22) (2016)