Juno Nam

According to our database, Juno Nam authored at least 14 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Scaling Autoregressive Models for Lattice Thermodynamics.

Xiaochen Du, Juno Nam, Sulin Liu, Rafael Gómez-Bombarelli

CoRR, March, 2026

Discrete Adjoint Schrödinger Bridge Sampler.

Wei Guo, Yuchen Zhu, Xiaochen Du, Juno Nam, Yongxin Chen, Rafael Gómez-Bombarelli, Guan-Horng Liu, Molei Tao, Jaemoo Choi

CoRR, February, 2026

Generalized Schrödinger Bridge on Graphs.

Panagiotis Theodoropoulos, Juno Nam, Evangelos A. Theodorou, Jaemoo Choi

CoRR, February, 2026

FragmentFlow: Scalable Transition State Generation for Large Molecules.

Ron Shprints, Peter Holderrieth, Juno Nam, Rafael Gómez-Bombarelli, Tommi S. Jaakkola

CoRR, February, 2026

2025

Enhancing Diffusion-Based Sampling with Molecular Collective Variables.

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

CoRR, October, 2025

Learning from the electronic structure of molecules across the periodic table.

Manasa Kaniselvan, Benjamin Kurt Miller, Meng Gao, Juno Nam, Daniel S. Levine

CoRR, October, 2025

Transferable Learning of Reaction Pathways from Geometric Priors.

Juno Nam, Miguel Steiner, Max Misterka, Soojung Yang, Avni P. Singhal, Rafael Gómez-Bombarelli

CoRR, April, 2025

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

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

Understanding active learning of molecular docking and its applications.

Jeonghyeon Kim, Juno Nam, Seongok Ryu

CoRR, 2024

Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials.

Juno Nam, Rafael Gómez-Bombarelli

CoRR, 2024

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

2016

Linking the Neural Machine Translation and the Prediction of Organic Chemistry Reactions.

Juno Nam, Jurae Kim

CoRR, 2016