1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
MeshDQN: A Deep Reinforcement Learning Framework for Improving Meshes in Computational Fluid Dynamics
Cooper Lorsung, Amir Barati Farimani
Meshing is a critical, but user-intensive process necessary for stable and accurate simulations in computational fluid dynamics (CFD). Mesh generation is often a bottleneck in CFD…
stat.ML2021★ 1 cited
Understanding Uncertainty in Bayesian Deep Learning
Cooper Lorsung
Neural Linear Models (NLM) are deep Bayesian models that produce predictive uncertainty by learning features from the data and then performing Bayesian linear regression over these…