Lusch, Bethany

1. AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification
   2021/10/26 by Romain Égelé, Egele, Romain, Romit Maulik +9 · 2 citations
   Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
2. Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks
   2024/09/12 by Barwey, Shivam, Pal, Pinaki, Patel, Saumil +5 · 4 citations
   #Computational Engineering #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Finance #Fluid Dynamics (physics.flu-dyn) #Machine Learning (cs.LG) #and Science (cs.CE)
3. Deploying deep learning in OpenFOAM with TensorFlow
   2020/12/01 by Maulik, Romit, Sharma, Himanshu, Patel, Saumil +2 · 1 citation
   #Computational Physics (physics.comp-ph) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Machine Learning (cs.LG) #Statistics and Probability (physics.data-an)
4. Efficient high-dimensional variational data assimilation with machine-learned reduced-order models
   2021/12/15 by Romit Maulik, Maulik, Romit, Vishwas Rao +14 · 1 citation
   Earth and Planetary Sciences · Environmental Science · Physics and Astronomy · #Climate variability and models #Dynamical Systems (math.DS) #FOS: Mathematics #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks
5. A turbulent eddy-viscosity surrogate modeling framework for\n Reynolds-Averaged Navier-Stokes simulations
   2019/10/23 by Romit Maulik, Maulik, Romit, Himanshu Sharma +8 · 1 citation
   Engineering · Physics and Astronomy · #Computational Fluid Dynamics and Aerodynamics #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Lattice Boltzmann Simulation Studies #Model Reduction and Neural Networks