Stephen Baek
Orcid: 0000-0002-4758-4539Affiliations:
- University of Iowa, Department of Industrial and System Engineering, Iowa City, IA, USA
- Seoul National University, School of Mechanical and Aerospace Engineering, South Korea (PhD 2013)
According to our database1,
Stephen Baek
authored at least 43 papers
between 2009 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2024
FedPAE: Peer-Adaptive Ensemble Learning for Asynchronous and Model-Heterogeneous Federated Learning.
CoRR, 2024
Comput. Methods Programs Biomed., 2024
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Challenges and Opportunities for Machine Learning in Multiscale Computational Modeling.
J. Comput. Inf. Sci. Eng., December, 2023
J. Mach. Learn. Res., 2023
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023
2022
Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions.
CoRR, 2022
A physics-aware deep learning model for energy localization in multiscale shock-to-detonation simulations of heterogeneous energetic materials.
CoRR, 2022
Physics-Aware Recurrent Convolutional (PARC) Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials.
CoRR, 2022
Enabling AI Innovation via Data and Model Sharing: An Overview of the Nsf Convergence Accelerator Track D.
AI Mag., 2022
Proceedings of the Future Technologies Conference, 2022
2021
Machine Learning Prediction of Fall Risk in Older Adults Using Timed Up and Go Test Kinematics.
Sensors, 2021
2020
Embedded spectral descriptors: learning the point-wise correspondence metric via Siamese neural networks.
J. Comput. Des. Eng., 2020
Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials.
CoRR, 2020
ZerNet: Convolutional Neural Networks on Arbitrary Surfaces Via Zernike Local Tangent Space Estimation.
Comput. Graph. Forum, 2020
2019
Modeling and Forecasting Short-Term Power Load With Copula Model and Deep Belief Network.
IEEE Trans. Emerg. Top. Comput. Intell., 2019
What does AI see? Deep segmentation networks discover biomarkers for lung cancer survival.
CoRR, 2019
NADS-Net: A Nimble Architecture for Driver and Seat Belt Detection via Convolutional Neural Networks.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019
2018
ZerNet: Convolutional Neural Networks on Arbitrary Surfaces via Zernike Local Tangent Space Estimation.
CoRR, 2018
Wall Stress Estimation of Cerebral Aneurysm based on Zernike Convolutional Neural Networks.
CoRR, 2018
Extreme Learning Machines for VISualization+R: Mastering Visualization with Target Variables.
Cogn. Comput., 2018
Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018
2017
Deep Spectral Descriptors: Learning the point-wise correspondence metric via Siamese deep neural networks.
CoRR, 2017
2016
ELMVIS+: Fast nonlinear visualization technique based on cosine distance and extreme learning machines.
Neurocomputing, 2016
Int. J. Comput. Aided Eng. Technol., 2016
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
2015
J. Comput. Des. Eng., 2015
2014
GaFinC: Gaze and Finger Control interface for 3D model manipulation in CAD application.
Comput. Aided Des., 2014
Automatic Detection of Inferior Alveolar Nerve Canal from Cone-Beam Computed Tomography Images for Dental Surgery Planning.
Proceedings of the Medicine Meets Virtual Reality 21 - NextMed, 2014
2013
Int. J. Comput. Aided Eng. Technol., 2013
Automated bone landmarks prediction on the femur using anatomical deformation technique.
Comput. Aided Des., 2013
2012
Comput. Aided Des., 2012
2010
Simul. Model. Pract. Theory, 2010
2009
Proceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry, 2009