On-device research index

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.

168,657 papers · 148 categories

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6 results for “cathodes”

Generative adversarial framework to calibrate excursion set models for the 3D morphology of all-solid-state battery cathodesstat.ML

Generative model calibrates 3D battery cathode morphologies from 2D images.

problem Calibrate 3D morphologies of all-solid-state battery cathodes from 2D microscopy images.

method Combining GANs with excursion sets of Gaussian random fields.

result Calibrated digital twins enable systematic exploration of morphological scenarios.

all-solid-state battery cathodes 3D morphology digital twins excursion sets

2025-03-21abs ↗pdf ↗

Careful analysis of XRD patterns with Attentionstat.ML

Extracts important peaks from XRD spectra using Attention mechanism.

problem Identifying significant peaks in XRD patterns for material properties.

method Convolutional neural network with Attention mechanism to analyze deep features.

result Selected lattice constant predicts cathodic material cell voltage.

XRD patterns Attention mechanism Convolutional neural network Lithium ion batteries Physical properties

2020-06-02abs ↗pdf ↗

Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solidsphysics.comp-ph

Equivariant graph neural networks predict electron density for molecules, liquids, and solids.

problem Predicting electron density for molecules, liquids, and solids using machine learning.

method Equivariant graph neural networks for predicting electron density at query points.

result The model predicts electron density with accuracy beyond state of the art and significantly faster than traditional DFT methods.

electron density machine learning graph neural networks density functional theory materials science

2021-12-01abs ↗pdf ↗

Uncertainty quantification of a multi-component Hall thruster model at varying facility pressuresstat.AP

Bayesian inference calibrates Hall thruster model uncertainty at varying pressures.

problem Quantifying uncertainty in a multi-component Hall thruster model at different facility pressures.

method Bayesian inference applied to calibrate and quantify prediction uncertainty in a coupled multi-component Hall thruster model.

result Model reduces predictive errors in thrust and discharge current by more than 50% compared to a previous model.

Bayesian inference Hall thruster uncertainty quantification pressure effects plasma properties

2025-07-10abs ↗pdf ↗

Variational Bayesian Optimal Experimental Design with Normalizing Flowscs.LG

vOED-NFs uses normalizing flows to improve Bayesian OED without likelihood evaluations.

problem Optimizing experiments to maximize information gain in model parameters.

method vOED-NFs combines variational approximations with normalizing flows for efficient EIG estimation.

result vOED-NFs achieves lower EIG estimation bias compared to previous methods.

Bayesian OED Normalizing Flows Monte Carlo Estimators Gradient Optimization Electrophoretic Deposition

2024-04-08abs ↗pdf ↗

Generative Multi-Objective Bayesian Optimization with Scalable Batch Evaluations for Sample-Efficient De Novo Molecular Designstat.ML

This work improves molecular design by efficiently selecting diverse candidate molecules.

problem Designing molecules that satisfy multiple conflicting objectives.

method A modular 'generate-then-optimize' framework using generative models and a novel acquisition function.

result Significant improvements in sample efficiency across synthetic and application-driven tasks.

molecular design Bayesian optimization generative models multi-objective scalable batch selection

2025-12-19abs ↗pdf ↗