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Ashley Lenau

Observed names: Ashley T. Lenau, Lenau, Ashley, Lenau, Ashley T., Lenau, Ashley T. [Los Alamos National Laboratory]; Scheinker, Alexander [Los Alamos National Laboratory]; Pokharel, Reeju [Los Alamos National Laboratory]; Niezgoda, S. R. [The Ohio State University]; Dimiduk, D. M. [BlueQuartz Software]
ORCID: 0009-0001-0371-512X
Observed ORCID: 0009-0001-0371-512X
OpenAlex ID: A5096292496
Microstructure-based variational deep material networks for robust uncertainty quantification in materials digital twins
2026 · Andreas E. Robertson, Samuel B. Inman, et al. · npj Computational Materials · 7
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Importance of Hyper-Parameter Optimization During Training of Physics-Informed Deep Learning Networks
2025 · Ashley Lenau, Dennis Dimiduk, et al. · Integrating materials and manufacturing innovation · 7
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Training variation of physically-informed deep learning models
2026 · Ashley Lenau, Dennis Dimiduk, et al. · Machine Learning Science and Technology · 1
Beyond Compression: Training Latent Representations for Stable Long-Horizon Rollout in Neural Surrogate Solvers
2026 · Robertson, Andreas E., Lenau, Ashley T., et al. · arXiv (Cornell University)
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mesoOSU/PB-GAN: PBGAN: Model Variation
2026 · Stephen Niezgoda, Ashley Lenau · Zenodo (CERN European Organization for Nuclear Research)
Author response for "Training variation of physically-informed deep learning models"
2026 · Lenau, Ashley, Dimiduk, Dennis, et al. · Publons reviews and discussion
Author response for "Training variation of physically-informed deep learning models"
2026 · Lenau, Ashley, Dimiduk, Dennis, et al. · Publons reviews and discussion
Investigating Deep Material Networks as Representative Microstructures for the Mechanical Behavior of Composites
2025 · Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States), Ashley Lenau, et al. · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
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Variational Deep Material Network: Enabling efficient aleatoric UQ in structure-property modeling
2025 · Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States), Andreas Robertson, et al. · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
Separable Uncertainty Quantification in Materials Experiments with Variational Deep Material Networks
2025 · Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States), Andreas Robertson, et al. · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
Full-field elastic strain tensor evolution of 3D polycrystals with recurrent neural networks and transfer learning
2025 · Ashley Lenau, Reeju Pokharel, et al. · Mechanics of Materials
Advantages and Limitations of using Physics Informed Deep Learning to Model Crystal Plasticity
2024 · Lenau, Ashley T. [Los Alamos National Laboratory]; Scheinker, Alexander [Los Alamos National Laboratory]; Pokharel, Reeju [Los Alamos National Laboratory]; Niezgoda, S. R. [The Ohio State University]; Dimiduk, D. M. [BlueQuartz Software] · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
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Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals
2024 · Ashley Lenau, USDOE National Nuclear Security Administration (NNSA), et al. · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
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Works count: 14
Citation count: 15
H-index: 2
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