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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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3 results for “wall-pressure”

Predicting the wall-shear stress and wall pressure through convolutional neural networksphysics.flu-dyn

Study uses neural networks to predict wall quantities in turbulent flows.

problem Predicting wall quantities in turbulent open channel flows.

method Training convolutional neural networks (FCN) and a proposed R-Net architecture to predict wall-shear-stress and wall pressure.

result R-Net architecture performs better and predicts wall quantities with around 10% error.

turbulent flow wall-shear-stress wall-pressure neural networks open channel flow

2023-03-01abs ↗pdf ↗

Convolutional-network models to predict wall-bounded turbulence from wall quantitiesphysics.flu-dyn

Convolutional networks predict turbulence from wall quantities.

problem Predicting turbulence fields from wall-shear-stress components and wall pressure.

method Two CNN models: FCN and FCN-POD, trained on DNS data.

result FCN and FCN-POD models outperform EPOD in predicting turbulence fields.

turbulence prediction wall-bounded turbulence convolutional neural networks DNS wall-shear-stress

2020-06-22abs ↗pdf ↗

Accelerating Hamiltonian Monte Carlo for Bayesian Inference in Neural Networks and Neural Operatorsstat.ML

Hybrid approach combines VI and HMC for efficient Bayesian inference in neural networks.

problem Computational demands and inaccuracies in Bayesian inference for neural networks.

method Combines VI and HMC, reducing parameter space and accelerating inference.

result Significantly reduces inference time for large neural networks, improving uncertainty quantification.

Hamiltonian Monte Carlo Bayesian inference Neural networks Uncertainty quantification Dimensionality reduction

2025-07-19abs ↗pdf ↗