2024
Estimating Position-Dependent and Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories: Existing Methods and Future Outlook
Domingues T, Coifman R, Haji-Akbari A. Estimating Position-Dependent and Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories: Existing Methods and Future Outlook. Journal Of Chemical Theory And Computation 2024, 20: 4427-4455. PMID: 38815171, DOI: 10.1021/acs.jctc.4c00148.Peer-Reviewed Original ResearchKernel-based methodsMolecular dynamicsMolecular dynamics trajectoriesAnisotropic diffusion tensorPhysicochemical properties of materialsClosed-form analytical solutionMD trajectoriesMobility statisticsComputational chemistryHeuristic extensionMD simulationsProperties of materialsAlgorithmDynamics trajectoriesDiffusion tensorEstimated diffusivityVariable spaceMaterial propertiesDiscretization techniqueNatural extensionPosition-dependentFokker-Planck equationSpatial binsAnalytical solutionTracer particles
2013
Diffusion Maps for Signal Processing: A Deeper Look at Manifold-Learning Techniques Based on Kernels and Graphs
Talmon R, Cohen I, Gannot S, Coifman R. Diffusion Maps for Signal Processing: A Deeper Look at Manifold-Learning Techniques Based on Kernels and Graphs. IEEE Signal Processing Magazine 2013, 30: 75-86. DOI: 10.1109/msp.2013.2250353.Peer-Reviewed Original ResearchParametric statistical inferenceDigital signal processing systemsMachine-learning approachesKernel-based methodsSignal processingManifold learning techniquesComputational capabilitiesSignal processing systemGraphical modelsStatistical inferenceMore computationSignal processing methodsBayesian networkDSP systemsEfficient algorithmProcessing systemComputational burdenLinear filterDiffusion mapsAlgorithmProcessing methodsTraditional methodsProcessingNetworkGraph