Audio-driven Nonlinear Video Diffusion

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We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...

The present research aims at understanding the mass transfer of air into water in a reversible pump turbine operating in condenser mode. In particular, the diffusion of oxygen through the water free-surface both in the vaneless gap between the impeller bla ...

Graph machine learning offers a powerful framework with natural applications in scientific fields such as chemistry, biology and material sciences. By representing data as a graph, we encode the prior knowledge that the data is composed of a set of entiti ...

For large-scale screening studies there is a need to estimate the diffusion of gas molecules in nanoporous materials more efficiently than (brute force) molecular dynamics. In particular for systems with low diffusion coefficients molecular dynamics can be ...

Diffusion is one of the most important phenomena studied in science ranging from physics to biology and, in abstract form, even in social sciences. In the field of materials science, diffusion in crystalline solids is of particular interest as it plays a p ...

We examine the diffusion of methane in the metal organic frameworks M-2(dobdc) (M = Mg, Ni, Zn; dobdc(4-) = 2,5-diwddo-1,4-benzenedicarboxylate) as a function of methane loading through a combination of nuclear magnetic resonance and molecular dynamics sim ...

A two-platform measurement system for realizing airborne thermography of the Lake Surface Water Temperature (LSWT) with ~0.8 m pixel resolution (sub-pixel satellite scale) is presented. It consists of a tethered Balloon Launched Imaging and Monitoring Plat ...

Gas diffusion electrodes (GDEs) help to reduce transport limitations in devices for electrochemical CO2 reduction. Homogenized modeling of such devices requires input of morphological characteristics and effective transport properties of the porous structu ...

Successful application of diffusion chronometry is based on detailed knowledge of diffusion parameters obtained from laboratory experiments, which also need to be upscaled to be applied to natural samples. While generally applicable, several examples of di ...

This study presents a self-supervised Bayesian Neural Network (BNN) framework using air-borne Acoustic Emission (AE) to identify different Laser Powder Bed Fusion (LPBF) process regimes such as Lack of Fusion, conduction mode, and keyhole without ground-tr ...

Audio-driven Nonlinear Video Diffusion

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Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Oxygen diffusion through air–water free surfaces in a pump–turbine operating in condenser mode

Equivariant Neural Architectures for Representing and Generating Graphs

Automated Multiscale Approach To Predict Self-Diffusion from a Potential Energy Field

Atomic scale volume and grain boundary diffusion elucidated by in situ STEM

Combined Nuclear Magnetic Resonance and Molecular Dynamics Study of Methane Adsorption in M-2(dobdc) Metal-Organic Frameworks

Achieving high-resolution thermal imagery in low-contrast lake surface waters by aerial remote sensing and image registration

Morphology and Transport Characterization of Catalyst Layers for CO2 Reduction

Diffusion timescale conundrum in contact metamorphism: Oxygen isotope and trace element profiles in dolomite

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring