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ORCIDRafael Gómez-Bombarelli
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- affiliation: Massachusetts Institute of Technology, Department of Materials Science and Engineering, Cambridge, MA, USA
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2020 – today
- 2025
[j9]Mingrou Xie
, Daniel Schwalbe-Koda, Yolanda Marcela Semanate-Esquivel, Estefanía Bello-Jurado, Alexander Hoffman, Omar Santiago-Reyes, Cecilia Paris, Manuel Moliner, Rafael Gómez-Bombarelli:
A comprehensive mapping of zeolite-template chemical space. Nat. Comput. Sci. 5(8): 661-674 (2025)- [c8]Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stärk, Yilun Xu, Tommi S. Jaakkola, Rafael Gómez-Bombarelli:
Think while You Generate: Discrete Diffusion with Planned Denoising. ICLR 2025 - [i40]Nofit Segal, Aviv Netanyahu, Kevin P. Greenman, Pulkit Agrawal, Rafael Gómez-Bombarelli:
Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules. CoRR abs/2502.05970 (2025) - [i39]Xiaochen Du, Mengren Liu, Jiayu Peng, Hoje Chun, Alexander Hoffman, Bilge Yildiz, Lin Li, Martin Z. Bazant, Rafael Gómez-Bombarelli:
Accelerating and enhancing thermodynamic simulations of electrochemical interfaces. CoRR abs/2503.17870 (2025) - [i38]Juno Nam, Miguel Steiner, Max Misterka, Soojung Yang, Avni P. Singhal, Rafael Gómez-Bombarelli:
Transferable Learning of Reaction Pathways from Geometric Priors. CoRR abs/2504.15370 (2025) - [i37]Utkarsh Utkarsh, Pengfei Cai, Alan Edelman, Rafael Gómez-Bombarelli, Christopher Vincent Rackauckas:
Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints. CoRR abs/2506.04171 (2025) - [i36]Seonghyun Park, Kiyoung Seong, Soojung Yang, Rafael Gómez-Bombarelli, Sungsoo Ahn:
Learning Collective Variables from Time-lagged Generation. CoRR abs/2507.07390 (2025) - [i35]Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang:
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR abs/2509.02661 (2025) - [i34]Elton Pan, Soonhyoung Kwon, Sulin Liu, Mingrou Xie, Alexander J. Hoffman, Yifei Duan, Thorben Prein, Killian Sheriff, Yuriy Roman-Leshkov, Manuel Moliner, Rafael Gómez-Bombarelli, Elsa A. Olivetti:
DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning. CoRR abs/2509.17094 (2025) - [i33]Juno Nam, Bálint Máté, Artur P. Toshev, Manasa Kaniselvan, Rafael Gómez-Bombarelli, Ricky T. Q. Chen, Brandon M. Wood, Guan-Horng Liu, Benjamin Kurt Miller:
Enhancing Diffusion-Based Sampling with Molecular Collective Variables. CoRR abs/2510.11923 (2025) - [i32]Sathya Edamadaka, Soojung Yang, Ju Li, Rafael Gómez-Bombarelli:
Universally Converging Representations of Matter Across Scientific Foundation Models. CoRR abs/2512.03750 (2025) - [i31]Nofit Segal, Akshay Subramanian, Mingda Li, Benjamin Kurt Miller, Rafael Gómez-Bombarelli:
The Loss Landscape of Powder X-Ray Diffraction-Based Structure Optimization Is Too Rough for Gradient Descent. CoRR abs/2512.04036 (2025) - 2024
- [i30]Soojung Yang, Juno Nam, Johannes C. B. Dietschreit, Rafael Gómez-Bombarelli:
Learning Collective Variables for Protein Folding with Labeled Data Augmentation through Geodesic Interpolation. CoRR abs/2402.01542 (2024) - [i29]Aik Rui Tan, Johannes C. B. Dietschreit, Rafael Gómez-Bombarelli:
Enhanced sampling of robust molecular datasets with uncertainty-based collective variables. CoRR abs/2402.03753 (2024) - [i28]Juno Nam, Rafael Gómez-Bombarelli:
Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials. CoRR abs/2404.10746 (2024) - [i27]Jiayu Peng, James K. Damewood, Jessica Karaguesian, Jaclyn R. Lunger, Rafael Gómez-Bombarelli:
Learning Ordering in Crystalline Materials with Symmetry-Aware Graph Neural Networks. CoRR abs/2409.13851 (2024) - [i26]Juno Nam, Sulin Liu, Gavin Winter, KyuJung Jun, Soojung Yang, Rafael Gómez-Bombarelli:
Flow Matching for Accelerated Simulation of Atomic Transport in Materials. CoRR abs/2410.01464 (2024) - [i25]Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stärk, Yilun Xu, Tommi S. Jaakkola, Rafael Gómez-Bombarelli:
Think While You Generate: Discrete Diffusion with Planned Denoising. CoRR abs/2410.06264 (2024) - [i24]Akshay Subramanian, Shuhui Qu, Cheol Woo Park, Sulin Liu, Janghwan Lee, Rafael Gómez-Bombarelli:
Efficient Generation of Molecular Clusters with Dual-Scale Equivariant Flow Matching. CoRR abs/2410.07539 (2024) - [i23]Akshay Subramanian, James K. Damewood, Juno Nam, Kevin P. Greenman, Avni P. Singhal, Rafael Gómez-Bombarelli:
Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search. CoRR abs/2410.08833 (2024) - [i22]Qibang Liu, Pengfei Cai, Diab W. Abueidda, Sagar Vyas, Seid Koric, Rafael Gómez-Bombarelli, Philippe H. Geubelle:
Univariate Conditional Variational Autoencoder for Morphogenic Patterns Design in Frontal Polymerization-Based Manufacturing. CoRR abs/2410.17518 (2024) - 2023
- [j8]Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli:
Mapping the Space of Photoswitchable Ligands and Photodruggable Proteins with Computational Modeling. J. Chem. Inf. Model. 63(18): 5794-5802 (2023) - [j7]Simon Axelrod, Rafael Gómez-Bombarelli:
Molecular machine learning with conformer ensembles. Mach. Learn. Sci. Technol. 4(3): 35025 (2023) - [j6]Nathan C. Frey, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gómez-Bombarelli, Connor W. Coley, Vijay Gadepally:
Neural scaling of deep chemical models. Nat. Mac. Intell. 5(11): 1297-1305 (2023) - [j5]Xiaochen Du, James K. Damewood, Jaclyn R. Lunger, Reisel Millan, Bilge Yildiz, Lin Li, Rafael Gómez-Bombarelli:
Machine-learning-accelerated simulations to enable automatic surface reconstruction. Nat. Comput. Sci. 3(12): 1034-1044 (2023) - [j4]Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie, Sinan Keten, Rafael Gómez-Bombarelli, Tommi S. Jaakkola:
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations. Trans. Mach. Learn. Res. 2023 (2023) - [c7]Martin Sípka, Johannes C. B. Dietschreit, Lukás Grajciar, Rafael Gómez-Bombarelli:
Differentiable Simulations for Enhanced Sampling of Rare Events. ICML 2023: 31990-32007 - [c6]Soojung Yang, Rafael Gómez-Bombarelli:
Chemically Transferable Generative Backmapping of Coarse-Grained Proteins. ICML 2023: 39277-39298 - [i21]Martin Sípka, Johannes C. B. Dietschreit, Lukás Grajciar, Rafael Gómez-Bombarelli:
Differentiable Simulations for Enhanced Sampling of Rare Events. CoRR abs/2301.03480 (2023) - [i20]Soojung Yang, Rafael Gómez-Bombarelli:
Chemically Transferable Generative Backmapping of Coarse-Grained Proteins. CoRR abs/2303.01569 (2023) - [i19]Akshay Subramanian, Kevin P. Greenman, Alexis Gervaix, Tzuhsiung Yang, Rafael Gómez-Bombarelli:
Automated patent extraction powers generative modeling in focused chemical spaces. CoRR abs/2303.08272 (2023) - [i18]Aik Rui Tan, Shingo Urata, Samuel Goldman, Johannes C. B. Dietschreit, Rafael Gómez-Bombarelli:
Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles. CoRR abs/2305.01754 (2023) - [i17]Xiaochen Du, James K. Damewood, Jaclyn R. Lunger, Reisel Millan, Bilge Yildiz, Lin Li, Rafael Gómez-Bombarelli:
Machine-learning-accelerated simulations enable heuristic-free surface reconstruction. CoRR abs/2305.07251 (2023) - 2022
- [j3]Somesh Mohapatra, Joyce An, Rafael Gómez-Bombarelli:
Chemistry-informed macromolecule graph representation for similarity computation, unsupervised and supervised learning. Mach. Learn. Sci. Technol. 3(1): 15028 (2022) - [c5]Shomik Verma, Shivam Kajale, Rafael Gómez-Bombarelli:
Machine learning for accurate and fast bandgap prediction of solid-state materials. HPEC 2022: 1-2 - [c4]Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess E. Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli:
Generative Coarse-Graining of Molecular Conformations. ICML 2022: 23213-23236 - [c3]Nathan C. Frey, Dan Zhao, Simon Axelrod, Michael Jones, David Bestor, Vijay Gadepally, Rafael Gómez-Bombarelli, Siddharth Samsi:
Energy-aware neural architecture selection and hyperparameter optimization. IPDPS Workshops 2022: 732-741 - [i16]Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess E. Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli:
Generative Coarse-Graining of Molecular Conformations. CoRR abs/2201.12176 (2022) - [i15]Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli:
Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential. CoRR abs/2207.11592 (2022) - [i14]Wujie Wang, Zhenghao Wu, Rafael Gómez-Bombarelli:
Learning Pair Potentials using Differentiable Simulations. CoRR abs/2209.07679 (2022) - [i13]Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie, Sinan Keten, Rafael Gómez-Bombarelli, Tommi S. Jaakkola:
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations. CoRR abs/2210.07237 (2022) - 2021
- [c2]Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang:
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. ICML 2021: 11537-11547 - [i12]Tian Xie, Arthur France-Lanord, Yanming Wang, Jeffrey Lopez, Michael Austin Stolberg, Megan Hill, Graham Michael Leverick, Rafael Gómez-Bombarelli, Jeremiah A. Johnson, Yang Shao-Horn, Jeffrey C. Grossman:
Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations. CoRR abs/2101.05339 (2021) - [i11]Daniel Schwalbe-Koda, Aik Rui Tan, Rafael Gómez-Bombarelli:
Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials. CoRR abs/2101.11588 (2021) - [i10]Somesh Mohapatra, Joyce An, Rafael Gómez-Bombarelli:
Chemistry-informed Macromolecule Graph Representation for Similarity Computation and Supervised Learning. CoRR abs/2103.02565 (2021) - [i9]Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang:
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. CoRR abs/2105.07246 (2021) - [i8]Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli:
Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential. CoRR abs/2108.04879 (2021) - 2020
- [j2]Somesh Mohapatra, Tzuhsiung Yang, Rafael Gómez-Bombarelli:
Reusability report: Designing organic photoelectronic molecules with descriptor conditional recurrent neural networks. Nat. Mach. Intell. 2(12): 749-752 (2020) - [i7]Wujie Wang, Simon Axelrod, Rafael Gómez-Bombarelli:
Differentiable Molecular Simulations for Control and Learning. CoRR abs/2003.00868 (2020) - [i6]Simon Axelrod, Rafael Gómez-Bombarelli:
GEOM: Energy-annotated molecular conformations for property prediction and molecular generation. CoRR abs/2006.05531 (2020) - [i5]Simon Axelrod, Rafael Gómez-Bombarelli:
Molecular machine learning with conformer ensembles. CoRR abs/2012.08452 (2020)
2010 – 2019
- 2019
- [j1]Francisco Javier Montáns, Francisco Chinesta, Rafael Gómez-Bombarelli, J. Nathan Kutz:
Complex Algorithms for Data-Driven Model Learning in Science and Engineering. Complex. 2019: 5040637:1-5040637:3 (2019) - [i4]Daniel Schwalbe-Koda, Rafael Gómez-Bombarelli:
Generative Models for Automatic Chemical Design. CoRR abs/1907.01632 (2019) - 2018
- [i3]Wujie Wang, Rafael Gómez-Bombarelli:
Variational Coarse-Graining for Molecular Dynamics. CoRR abs/1812.02706 (2018) - 2016
- [i2]Rafael Gómez-Bombarelli, David Duvenaud, José Miguel Hernández-Lobato, Jorge Aguilera-Iparraguirre, Timothy D. Hirzel, Ryan P. Adams, Alán Aspuru-Guzik:
Automatic chemical design using a data-driven continuous representation of molecules. CoRR abs/1610.02415 (2016) - 2015
- [c1]David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams:
Convolutional Networks on Graphs for Learning Molecular Fingerprints. NIPS 2015: 2224-2232 - [i1]David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams:
Convolutional Networks on Graphs for Learning Molecular Fingerprints. CoRR abs/1509.09292 (2015)
Coauthor Index
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