Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery S Kim, PY Lu, S Mukherjee, M Gilbert, L Jing, V Čeperić, M Soljačić IEEE Transactions on Neural Networks and Learning Systems, 2020 | 172 | 2020 |
Enhanced Strain Coupling of Nitrogen-Vacancy Spins to Nanoscale Diamond Cantilevers S Meesala, YI Sohn, HA Atikian, S Kim, MJ Burek, JT Choy, M Lončar Phys. Rev. Applied 5 (3), 2016 | 121 | 2016 |
Extracting interpretable physical parameters from spatiotemporal systems using unsupervised learning PY Lu, S Kim, M Soljačić Physical Review X 10 (3), 031056, 2020 | 70 | 2020 |
Tough iron-based bulk metallic glass alloys ST Kim, MD Demetriou, WL Johnson US Patent 8,911,572, 2014 | 55 | 2014 |
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure S Kim, PY Lu, C Loh, J Smith, J Snoek, M Soljacic Transactions of Machine Learning Research, 2021 | 33* | 2021 |
Fast Neural Models for Symbolic Regression at Scale A Costa, R Dangovski, O Dugan, S Kim, P Goyal, M Soljačić, J Jacobson arXiv preprint arXiv:2007.10784, 2020 | 23* | 2020 |
In-Situ Monitoring and Modeling of Metal Additive Manufacturing Powder Bed Fusion J Alldredge, J Soltwinski, S Storck, S Kim, A Goldberg Review of Progress in Quantitative Nondestructive Evaluation 1949 (1), 020007, 2018 | 16 | 2018 |
Luneburg Lens for Wide-Angle Chip-Scale Optical Beam Steering S Kim, J Sloan, JJ López, D Kharas, J Herd, S Bramhavar, P Juodawlkis, ... CLEO: Science and Innovations, SF3N. 7, 2019 | 14 | 2019 |
Surrogate-and invariance-boosted contrastive learning for data-scarce applications in science C Loh, T Christensen, R Dangovski, S Kim, M Soljačić Nature Communications 13 (1), 4223, 2022 | 13 | 2022 |
Deep learning and symbolic regression for discovering parametric equations M Zhang, S Kim, PY Lu, M Soljačić IEEE Transactions on Neural Networks and Learning Systems, 2023 | 12 | 2023 |
Automated discovery and optimization of 3D topological photonic crystals S Kim, T Christensen, SG Johnson, M Soljacic ACS Photonics 10 (4), 861-874, 2023 | 7 | 2023 |
Tunable Superconducting Cavity using Superconducting Quantum Interference Device Metamaterials S Kim, D Shrekenhamer, K McElroy, A Strikwerda, J Alldredge Scientific Reports 9 (1), 4630, 2019 | 7 | 2019 |
High impedance holographic metasurfaces for conformal and high gain antenna applications S Kim, D Shrekenhamer, J Will, R Awadallah, J Miragliotta 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2018 | 7 | 2018 |
Hydrogen diffusion behavior and vacancy interaction behavior in OsO2 and RuO2 by ab initio calculations S Kim, W Lai Computational Materials Science 102, 14-20, 2015 | 4 | 2015 |
Interpretable Neuroevolutionary Models for Learning Non-Differentiable Functions and Programs A Costa, R Dangovski, S Kim, P Goyal, M Soljačić, J Jacobson arXiv preprint arXiv:2007.10784, 2020 | 3 | 2020 |
Strain coupling of diamond nitrogen vacancy centers to nanomechanical resonators S Meesala, YI Sohn, HA Atikian, MJ Burek, S Kim, J Choy, M Loncar CLEO: QELS_Fundamental Science, FTh3B. 4, 2015 | 3 | 2015 |
Multimodal Learning for Crystalline Materials V Moro, C Loh, R Dangovski, A Ghorashi, A Ma, Z Chen, PY Lu, ... arXiv preprint arXiv:2312.00111, 2023 | 1 | 2023 |
Thermally tunable infrared metasurfaces D Shrekenhamer, K S. J., C L. J., LB Ruppalt, JG Champlain, ... Eleventh International Congress on Engineered Material Platforms for Novel …, 2017 | 1 | 2017 |
Sb2S3 nanostructured dynamic optical metasurfaces RC Bruce, A Podpirka, G Hunt, C Gutgsell, S Kim, J Miragliotta, ... Advanced Optics for Imaging Applications: UV through LWIR IX 13042, 1304202, 2024 | | 2024 |
Deep Learning and Symbolic Regression for Discovering Parametric Equations S Kim, M Zhang, PY Lu, M Soljacic ICML 2022 2nd AI for Science Workshop, 2022 | | 2022 |