Convolutional Networks on Graphs for Learning Molecular Fingerprints. - David Duvenaud; Dougal Maclaurin; Jorge Aguilera-Iparraguirre; Rafael Gómez-Bombarelli; Timothy Hirzel; Alán Aspuru-Guzik; Ryan P. Adams (NIPS, 2015)

Automatic chemical design using a data-driven continuous representation of molecules. - Rafael Gómez-Bombarelli; David Duvenaud; José Miguel Hernández-Lobato; Jorge Aguilera-Iparraguirre; Timothy D. Hirzel; Ryan P. Adams; Alán Aspuru-Guzik (CoRR, 2016)

Variational Coarse-Graining for Molecular Dynamics. - Wujie Wang; Rafael Gómez-Bombarelli (CoRR, 2018)

Complex Algorithms for Data-Driven Model Learning in Science and Engineering. - Francisco Javier Montáns; Francisco Chinesta; Rafael Gómez-Bombarelli; J. Nathan Kutz (Complex., 2019)

Generative Models for Automatic Chemical Design. - Daniel Schwalbe-Koda; Rafael Gómez-Bombarelli (CoRR, 2019)

Differentiable Molecular Simulations for Control and Learning. - Wujie Wang; Simon Axelrod; Rafael Gómez-Bombarelli (CoRR, 2020)

GEOM: Energy-annotated molecular conformations for property prediction and molecular generation. - Simon Axelrod; Rafael Gómez-Bombarelli (CoRR, 2020)

Reusability report: Designing organic photoelectronic molecules with descriptor conditional recurrent neural networks. - Somesh Mohapatra; Tzuhsiung Yang; Rafael Gómez-Bombarelli (Nat. Mach. Intell., 2020)

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. - Minkai Xu; Wujie Wang; Shitong Luo; Chence Shi; Yoshua Bengio; Rafael Gómez-Bombarelli; Jian Tang 005 (ICML, 2021)

Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations. - Tian Xie 002; 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 (CoRR, 2021)

Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials. - Daniel Schwalbe-Koda; Aik Rui Tan; Rafael Gómez-Bombarelli (CoRR, 2021)

Chemistry-informed Macromolecule Graph Representation for Similarity Computation and Supervised Learning. - Somesh Mohapatra; Joyce An; Rafael Gómez-Bombarelli (CoRR, 2021)

Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential. - Simon Axelrod; Eugene Shakhnovich; Rafael Gómez-Bombarelli (CoRR, 2021)

Machine learning for accurate and fast bandgap prediction of solid-state materials. - Shomik Verma; Shivam Kajale; Rafael Gómez-Bombarelli (HPEC, 2022)

Generative Coarse-Graining of Molecular Conformations. - Wujie Wang; Minkai Xu; Chen Cai; Benjamin Kurt Miller; Tess E. Smidt; Yusu Wang 001; Jian Tang 005; Rafael Gómez-Bombarelli (ICML, 2022)

Energy-aware neural architecture selection and hyperparameter optimization. - Nathan C. Frey; Dan Zhao 007; Simon Axelrod; Michael Jones 001; David Bestor; Vijay Gadepally; Rafael Gómez-Bombarelli; Siddharth Samsi (IPDPS Workshops, 2022)

Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential. - Simon Axelrod; Eugene Shakhnovich; Rafael Gómez-Bombarelli (CoRR, 2022)

Learning Pair Potentials using Differentiable Simulations. - Wujie Wang; Zhenghao Wu; Rafael Gómez-Bombarelli (CoRR, 2022)

Chemistry-informed macromolecule graph representation for similarity computation, unsupervised and supervised learning. - Somesh Mohapatra; Joyce An; Rafael Gómez-Bombarelli (Mach. Learn. Sci. Technol., 2022)

Differentiable Simulations for Enhanced Sampling of Rare Events. - Martin Sípka; Johannes C. B. Dietschreit; Lukás Grajciar; Rafael Gómez-Bombarelli (ICML, 2023)

Chemically Transferable Generative Backmapping of Coarse-Grained Proteins. - Soojung Yang; Rafael Gómez-Bombarelli (ICML, 2023)

Automated patent extraction powers generative modeling in focused chemical spaces. - Akshay Subramanian; Kevin P. Greenman; Alexis Gervaix; Tzuhsiung Yang; Rafael Gómez-Bombarelli (CoRR, 2023)

Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles. - Aik Rui Tan; Shingo Urata; Samuel Goldman; Johannes C. B. Dietschreit; Rafael Gómez-Bombarelli (CoRR, 2023)

Machine-learning-accelerated simulations enable heuristic-free surface reconstruction. - Xiaochen Du; James K. Damewood; Jaclyn R. Lunger; Reisel Millan; Bilge Yildiz; Lin Li; Rafael Gómez-Bombarelli (CoRR, 2023)

Machine-learning-accelerated simulations to enable automatic surface reconstruction. - Xiaochen Du; James K. Damewood; Jaclyn R. Lunger; Reisel Millan; Bilge Yildiz; Lin Li; Rafael Gómez-Bombarelli (Nat. Comput. Sci., 2023)

Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations. - Xiang Fu 005; Zhenghao Wu; Wujie Wang; Tian Xie 002; Sinan Keten; Rafael Gómez-Bombarelli; Tommi S. Jaakkola (Trans. Mach. Learn. Res., 2023)

Mapping the Space of Photoswitchable Ligands and Photodruggable Proteins with Computational Modeling. - Simon Axelrod; Eugene Shakhnovich; Rafael Gómez-Bombarelli (J. Chem. Inf. Model., 2023)

Molecular machine learning with conformer ensembles. - Simon Axelrod; Rafael Gómez-Bombarelli (Mach. Learn. Sci. Technol., 2023)

Neural scaling of deep chemical models. - Nathan C. Frey; Ryan Soklaski; Simon Axelrod; Siddharth Samsi; Rafael Gómez-Bombarelli; Connor W. Coley; Vijay Gadepally (Nat. Mac. Intell., 2023)

Learning Collective Variables for Protein Folding with Labeled Data Augmentation through Geodesic Interpolation. - Soojung Yang; Juno Nam; Johannes C. B. Dietschreit; Rafael Gómez-Bombarelli (CoRR, 2024)

Enhanced sampling of robust molecular datasets with uncertainty-based collective variables. - Aik Rui Tan; Johannes C. B. Dietschreit; Rafael Gómez-Bombarelli (CoRR, 2024)

Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials. - Juno Nam; Rafael Gómez-Bombarelli (CoRR, 2024)

Learning Ordering in Crystalline Materials with Symmetry-Aware Graph Neural Networks. - Jiayu Peng; James K. Damewood; Jessica Karaguesian; Jaclyn R. Lunger; Rafael Gómez-Bombarelli (CoRR, 2024)

Flow Matching for Accelerated Simulation of Atomic Transport in Materials. - Juno Nam; Sulin Liu; Gavin Winter; KyuJung Jun; Soojung Yang; Rafael Gómez-Bombarelli (CoRR, 2024)

Efficient Generation of Molecular Clusters with Dual-Scale Equivariant Flow Matching. - Akshay Subramanian; Shuhui Qu; Cheol Woo Park; Sulin Liu; Janghwan Lee; Rafael Gómez-Bombarelli (CoRR, 2024)

Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search. - Akshay Subramanian; James K. Damewood; Juno Nam; Kevin P. Greenman; Avni P. Singhal; Rafael Gómez-Bombarelli (CoRR, 2024)

Univariate Conditional Variational Autoencoder for Morphogenic Patterns Design in Frontal Polymerization-Based Manufacturing. - Qibang Liu; Pengfei Cai; Diab W. Abueidda; Sagar Vyas; Seid Koric; Rafael Gómez-Bombarelli; Philippe H. Geubelle (CoRR, 2024)

Think while You Generate: Discrete Diffusion with Planned Denoising. - Sulin Liu; Juno Nam; Andrew Campbell; Hannes Stärk; Yilun Xu; Tommi S. Jaakkola; Rafael Gómez-Bombarelli (ICLR, 2025)

Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules. - Nofit Segal; Aviv Netanyahu; Kevin P. Greenman; Pulkit Agrawal 001; Rafael Gómez-Bombarelli (CoRR, 2025)

Accelerating and enhancing thermodynamic simulations of electrochemical interfaces. - Xiaochen Du; Mengren Liu; Jiayu Peng; Hoje Chun; Alexander Hoffman; Bilge Yildiz; Lin Li; Martin Z. Bazant; Rafael Gómez-Bombarelli (CoRR, 2025)

Transferable Learning of Reaction Pathways from Geometric Priors. - Juno Nam; Miguel Steiner; Max Misterka; Soojung Yang; Avni P. Singhal; Rafael Gómez-Bombarelli (CoRR, 2025)

Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints. - Utkarsh Utkarsh; Pengfei Cai; Alan Edelman; Rafael Gómez-Bombarelli; Christopher Vincent Rackauckas (CoRR, 2025)

Learning Collective Variables from Time-lagged Generation. - Seonghyun Park 004; Kiyoung Seong; Soojung Yang; Rafael Gómez-Bombarelli; Sungsoo Ahn (CoRR, 2025)