| Ddsl: Deep differentiable simplex layer for learning geometric signals C Jiang, D Lansigan, P Marcus, M Nießner Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 15 | 2019 |
| Non-locality of mean scalar transport in two-dimensional Rayleigh–Taylor instability using the macroscopic forcing method DLOL Lavacot, J Liu, H Williams, BE Morgan, A Mani Journal of Fluid Mechanics 985, A47, 2024 | 4 | 2024 |
| A Model Form for Reynolds Stress Decay Informed by Analysis of Anisotropically Forced Homogeneous Turbulence T Homan, O Shende, DL Lavacot, A Mani Bulletin of the American Physical Society, 2023 | 1 | 2023 |
| Continuing Investigations of Nonlocality in Rayleigh-Taylor Instability Using the Macroscopic Forcing Method DL Lavacot, J Liu, B Morgan, A Mani Bulletin of the American Physical Society 67, 2022 | 1 | 2022 |
| Assessment of RANS models for Rayleigh-Taylor mixing using the Macroscopic Forcing Method DL Lavacot, J Liu, B Morgan, A Mani Bulletin of the American Physical Society, 2023 | | 2023 |
| Evaluating the Importance of Nonlocal Eddy Diffusivity for Rayleigh Taylor Instability DL Lansigan, A Mani, B Morgan, J Liu, H Williams APS Division of Fluid Dynamics Meeting Abstracts, E11. 009, 2021 | | 2021 |
| An Accelerated Macroscopic Forcing Method for Determining Eddy Viscosity Operators DL Lansigan, D Park, A Mani APS Division of Fluid Dynamics Meeting Abstracts, X11. 009, 2020 | | 2020 |
| DDSL: Deep Differentiable Simplex Layer for Learning Geometric Signals DL Ona Lansigan, P Marcus, M Nießner arXiv e-prints, arXiv: 1901.11082, 2019 | | 2019 |
| Neural Network Powered Adjoint Methods-Gradient Based Shape Optimization with Deep Learning D Lansigan, C Jiang, P Marcus Bulletin of the American Physical Society 63, 2018 | | 2018 |
| Student Design Projects to Improve Spatial Visualization Ability S McMains, S Shonkwiler, M Ansell, T Bronars, S Goldberg, S Hua, ... | | |
