Rafael Gómez-Bombarelli

63 papers A* 5Journal 55Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Priori Sampling of Transition States with Guided Diffusion. CoRR Hyukjun Lim, Soojung Yang, Lucas Pinède, Miguel Steiner, Yuanqi Du, Rafael Gómez-Bombarelli
2026	J	`jnl`	Discrete Adjoint Schrödinger Bridge Sampler. CoRR Wei Guo, Yuchen Zhu, Xiaochen Du, Juno Nam, Yongxin Chen, Rafael Gómez-Bombarelli, Guan-Horng Liu, Molei Tao, Jaemoo Choi
2026	J	`jnl`	FragmentFlow: Scalable Transition State Generation for Large Molecules. CoRR Ron Shprints, Peter Holderrieth, Juno Nam, Rafael Gómez-Bombarelli, Tommi S. Jaakkola
2026	J	`jnl`	Scaling Autoregressive Models for Lattice Thermodynamics. CoRR Xiaochen Du, Juno Nam, Sulin Liu, Rafael Gómez-Bombarelli
2026	J	`jnl`	Self-Conditioned Denoising for Atomistic Representation Learning. CoRR Tynan Perez, Rafael Gómez-Bombarelli
2026	J	`jnl`	Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials. CoRR Alex Morehead, Miruna T. Cretu, Antonia Panescu, Rishabh Anand, Maurice Weiler, Tynan Perez, Samuel M. Blau, Steven Farrell, Wahid Bhimji, Anubhav Jain, Hrushikesh Sahasrabuddhe, Pietro Lio, Tommi S. Jaakkola, Rafael Gómez-Bombarelli, Rex Ying, N. Benjamin Erichson, Michael W. Mahoney
2025	J	`jnl`	A comprehensive mapping of zeolite-template chemical space. Nat. Comput. Sci. Mingrou Xie, Daniel Schwalbe-Koda, Yolanda Marcela Semanate-Esquivel, Estefanía Bello-Jurado, Alexander Hoffman, Omar Santiago-Reyes, Cecilia Paris, Manuel Moliner, Rafael Gómez-Bombarelli
2025	J	`jnl`	Accelerating and enhancing thermodynamic simulations of electrochemical interfaces. CoRR Xiaochen Du, Mengren Liu, Jiayu Peng, Hoje Chun, Alexander Hoffman, Bilge Yildiz, Lin Li, Martin Z. Bazant, Rafael Gómez-Bombarelli
2025	J	`jnl`	DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning. CoRR 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
2025	J	`jnl`	Enhancing Diffusion-Based Sampling with Molecular Collective Variables. CoRR 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
2025	J	`jnl`	Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules. CoRR Nofit Segal, Aviv Netanyahu, Kevin P. Greenman, Pulkit Agrawal, Rafael Gómez-Bombarelli
2025	J	`jnl`	Learning Collective Variables from Time-lagged Generation. CoRR Seonghyun Park, Kiyoung Seong, Soojung Yang, Rafael Gómez-Bombarelli, Sungsoo Ahn
2025	J	`jnl`	Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints. CoRR Utkarsh Utkarsh, Pengfei Cai, Alan Edelman, Rafael Gómez-Bombarelli, Christopher Vincent Rackauckas
2025	J	`jnl`	The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR 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
2025	J	`jnl`	The Loss Landscape of Powder X-Ray Diffraction-Based Structure Optimization Is Too Rough for Gradient Descent. CoRR Nofit Segal, Akshay Subramanian, Mingda Li, Benjamin Kurt Miller, Rafael Gómez-Bombarelli
2025	A*	`conf`	Think while You Generate: Discrete Diffusion with Planned Denoising. ICLR Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stärk, Yilun Xu, Tommi S. Jaakkola, Rafael Gómez-Bombarelli
2025	J	`jnl`	Transferable Learning of Reaction Pathways from Geometric Priors. CoRR Juno Nam, Miguel Steiner, Max Misterka, Soojung Yang, Avni P. Singhal, Rafael Gómez-Bombarelli
2025	J	`jnl`	Universally Converging Representations of Matter Across Scientific Foundation Models. CoRR Sathya Edamadaka, Soojung Yang, Ju Li, Rafael Gómez-Bombarelli
2024	J	`jnl`	Efficient Generation of Molecular Clusters with Dual-Scale Equivariant Flow Matching. CoRR Akshay Subramanian, Shuhui Qu, Cheol Woo Park, Sulin Liu, Janghwan Lee, Rafael Gómez-Bombarelli
2024	J	`jnl`	Enhanced sampling of robust molecular datasets with uncertainty-based collective variables. CoRR Aik Rui Tan, Johannes C. B. Dietschreit, Rafael Gómez-Bombarelli
2024	J	`jnl`	Flow Matching for Accelerated Simulation of Atomic Transport in Materials. CoRR Juno Nam, Sulin Liu, Gavin Winter, KyuJung Jun, Soojung Yang, Rafael Gómez-Bombarelli
2024	J	`jnl`	Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials. CoRR Juno Nam, Rafael Gómez-Bombarelli
2024	J	`jnl`	Learning Collective Variables for Protein Folding with Labeled Data Augmentation through Geodesic Interpolation. CoRR Soojung Yang, Juno Nam, Johannes C. B. Dietschreit, Rafael Gómez-Bombarelli
2024	J	`jnl`	Learning Ordering in Crystalline Materials with Symmetry-Aware Graph Neural Networks. CoRR Jiayu Peng, James K. Damewood, Jessica Karaguesian, Jaclyn R. Lunger, Rafael Gómez-Bombarelli
2024	J	`jnl`	Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search. CoRR Akshay Subramanian, James K. Damewood, Juno Nam, Kevin P. Greenman, Avni P. Singhal, Rafael Gómez-Bombarelli
2024	J	`jnl`	Think While You Generate: Discrete Diffusion with Planned Denoising. CoRR Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stärk, Yilun Xu, Tommi S. Jaakkola, Rafael Gómez-Bombarelli
2024	J	`jnl`	Univariate Conditional Variational Autoencoder for Morphogenic Patterns Design in Frontal Polymerization-Based Manufacturing. CoRR Qibang Liu, Pengfei Cai, Diab W. Abueidda, Sagar Vyas, Seid Koric, Rafael Gómez-Bombarelli, Philippe H. Geubelle
2023	J	`jnl`	Automated patent extraction powers generative modeling in focused chemical spaces. CoRR Akshay Subramanian, Kevin P. Greenman, Alexis Gervaix, Tzuhsiung Yang, Rafael Gómez-Bombarelli
2023	A*	`conf`	Chemically Transferable Generative Backmapping of Coarse-Grained Proteins. ICML Soojung Yang, Rafael Gómez-Bombarelli
2023	J	`jnl`	Chemically Transferable Generative Backmapping of Coarse-Grained Proteins. CoRR Soojung Yang, Rafael Gómez-Bombarelli
2023	A*	`conf`	Differentiable Simulations for Enhanced Sampling of Rare Events. ICML Martin Sípka, Johannes C. B. Dietschreit, Lukás Grajciar, Rafael Gómez-Bombarelli
2023	J	`jnl`	Differentiable Simulations for Enhanced Sampling of Rare Events. CoRR Martin Sípka, Johannes C. B. Dietschreit, Lukás Grajciar, Rafael Gómez-Bombarelli
2023	J	`jnl`	Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations. Trans. Mach. Learn. Res. Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie, Sinan Keten, Rafael Gómez-Bombarelli, Tommi S. Jaakkola
2023	J	`jnl`	Machine-learning-accelerated simulations enable heuristic-free surface reconstruction. CoRR Xiaochen Du, James K. Damewood, Jaclyn R. Lunger, Reisel Millan, Bilge Yildiz, Lin Li, Rafael Gómez-Bombarelli
2023	J	`jnl`	Machine-learning-accelerated simulations to enable automatic surface reconstruction. Nat. Comput. Sci. Xiaochen Du, James K. Damewood, Jaclyn R. Lunger, Reisel Millan, Bilge Yildiz, Lin Li, Rafael Gómez-Bombarelli
2023	J	`jnl`	Mapping the Space of Photoswitchable Ligands and Photodruggable Proteins with Computational Modeling. J. Chem. Inf. Model. Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
2023	J	`jnl`	Molecular machine learning with conformer ensembles. Mach. Learn. Sci. Technol. Simon Axelrod, Rafael Gómez-Bombarelli
2023	J	`jnl`	Neural scaling of deep chemical models. Nat. Mac. Intell. Nathan C. Frey, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gómez-Bombarelli, Connor W. Coley, Vijay Gadepally
2023	J	`jnl`	Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles. CoRR Aik Rui Tan, Shingo Urata, Samuel Goldman, Johannes C. B. Dietschreit, Rafael Gómez-Bombarelli
2022	J	`jnl`	Chemistry-informed macromolecule graph representation for similarity computation, unsupervised and supervised learning. Mach. Learn. Sci. Technol. Somesh Mohapatra, Joyce An, Rafael Gómez-Bombarelli
2022	—	`conf`	Energy-aware neural architecture selection and hyperparameter optimization. IPDPS Workshops Nathan C. Frey, Dan Zhao, Simon Axelrod, Michael Jones, David Bestor, Vijay Gadepally, Rafael Gómez-Bombarelli, Siddharth Samsi
2022	J	`jnl`	Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations. CoRR Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie, Sinan Keten, Rafael Gómez-Bombarelli, Tommi S. Jaakkola
2022	A*	`conf`	Generative Coarse-Graining of Molecular Conformations. ICML Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess E. Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli
2022	J	`jnl`	Generative Coarse-Graining of Molecular Conformations. CoRR Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess E. Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli
2022	J	`jnl`	Learning Pair Potentials using Differentiable Simulations. CoRR Wujie Wang, Zhenghao Wu, Rafael Gómez-Bombarelli
2022	—	`conf`	Machine learning for accurate and fast bandgap prediction of solid-state materials. HPEC Shomik Verma, Shivam Kajale, Rafael Gómez-Bombarelli
2022	J	`jnl`	Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential. CoRR Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
2021	J	`jnl`	Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations. CoRR 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
2021	J	`jnl`	Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials. CoRR Daniel Schwalbe-Koda, Aik Rui Tan, Rafael Gómez-Bombarelli
2021	A*	`conf`	An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. ICML Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang
2021	J	`jnl`	An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. CoRR Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang
2021	J	`jnl`	Chemistry-informed Macromolecule Graph Representation for Similarity Computation and Supervised Learning. CoRR Somesh Mohapatra, Joyce An, Rafael Gómez-Bombarelli
2021	J	`jnl`	Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential. CoRR Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
2020	J	`jnl`	Differentiable Molecular Simulations for Control and Learning. CoRR Wujie Wang, Simon Axelrod, Rafael Gómez-Bombarelli
2020	J	`jnl`	GEOM: Energy-annotated molecular conformations for property prediction and molecular generation. CoRR Simon Axelrod, Rafael Gómez-Bombarelli
2020	J	`jnl`	Molecular machine learning with conformer ensembles. CoRR Simon Axelrod, Rafael Gómez-Bombarelli
2020	J	`jnl`	Reusability report: Designing organic photoelectronic molecules with descriptor conditional recurrent neural networks. Nat. Mach. Intell. Somesh Mohapatra, Tzuhsiung Yang, Rafael Gómez-Bombarelli
2019	J	`jnl`	Complex Algorithms for Data-Driven Model Learning in Science and Engineering. Complex. Francisco Javier Montáns, Francisco Chinesta, Rafael Gómez-Bombarelli, J. Nathan Kutz
2019	J	`jnl`	Generative Models for Automatic Chemical Design. CoRR Daniel Schwalbe-Koda, Rafael Gómez-Bombarelli
2018	J	`jnl`	Variational Coarse-Graining for Molecular Dynamics. CoRR Wujie Wang, Rafael Gómez-Bombarelli
2016	J	`jnl`	Automatic chemical design using a data-driven continuous representation of molecules. CoRR Rafael Gómez-Bombarelli, David Duvenaud, José Miguel Hernández-Lobato, Jorge Aguilera-Iparraguirre, Timothy D. Hirzel, Ryan P. Adams, Alán Aspuru-Guzik
2015	—	`conf`	Convolutional Networks on Graphs for Learning Molecular Fingerprints. NIPS David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams
2015	J	`jnl`	Convolutional Networks on Graphs for Learning Molecular Fingerprints. CoRR David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams