Contracting Skeletal Kinematics for Human-Related Video Anomaly
Detection
January 23, 2023
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Computer Science
Computer Vision and Pattern Recognition
Detecting the anomaly of human behavior is paramount to timely recognizing
endangering situations, such as street fights or elderly falls. However,
anomaly detection is complex since anomalous events are rare and because it is
an open set r...
Techniques for Solving Static Klein-Gordon Equation with
Self-Interaction λϕ4 and Arbitrary Spherical Source Terms
January 23, 2023
Physics
Computational Physics
High Energy Physics - Phenomenology
Classical Physics
The Klein-Gordon equation for a scalar field sourced by a static spherically
symmetric background is an interesting second-order differential equation with
applications in particle physics, astrophysics, and elsewhere. Here we present
stati...
Scalable Spin Squeezing from Finite Temperature Easy-plane Magnetism
January 23, 2023
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Physics
Quantum Physics
Quantum Gases
Strongly Correlated Electrons
Atomic Physics
Spin squeezing is a form of entanglement that reshapes the quantum projection
noise to improve measurement precision. Here, we provide numerical and analytic
evidence for the following conjecture: any Hamiltonian exhibiting finite
temperatu...
Inference of the optical depth to reionization τ from
Planck CMB maps with convolutional neural networks
January 23, 2023
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Physics
Cosmology and Nongalactic Astrophysics
The optical depth to reionization, τ, is the least constrained parameter
of the cosmological ΛCDM model. To date, its most precise value is
inferred from large-scale polarized CMB power spectra from the Planck
High-Freq...
Perturbation-theory informed integrators for cosmological simulations
January 23, 2023
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Physics
Cosmology and Nongalactic Astrophysics
Instrumentation and Methods for Astrophysics
Computational Physics
Large-scale cosmological simulations are an indispensable tool for modern
cosmology. To enable model-space exploration, fast and accurate predictions are
critical. In this paper, we show that the performance of such simulations can
be furth...
Random models for singular SPDEs
January 23, 2023
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Mathematics
Probability
Analysis of PDEs
We give a proof of the convergence of the BHZ renormalized model associated
with the generalized (KPZ) equation that does not require the full strength of
the BPHZ renormalisation. Our approach is based on a convenient form of chaos
decompo...
Topological Learning in Multi-Class Data Sets
January 23, 2023
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Computer Science
Physics
Machine Learning
Data Analysis, Statistics and Probability
We specialize techniques from topological data analysis to the problem of
characterizing the topological complexity (as defined in the body of the paper)
of a multi-class data set. As a by-product, a topological classifier is defined
that u...
Near zero-field microwave-free magnetometry with ensembles of
nitrogen-vacancy centers in diamond
January 23, 2023
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Physics
Mesoscale and Nanoscale Physics
Applied Physics
We study cross-relaxation features near zero magnetic field with ensembles of
nitrogen-vacancy (NV) centers in diamond and examine their properties in
samples with a range (0.9 ppm - 16.0 ppm) of NV concentrations. The observed
NV-NV cross-...
Flexible Modeling of Demographic Transition Processes with a Bayesian
Hierarchical B-splines Model
January 23, 2023
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Statistics
Methodology
Several demographic and health indicators, including the total fertility rate
(TFR) and modern contraceptive use rate (mCPR), evolve similarly over time,
characterized by a transition between stable states. Existing approaches for
estimatio...
Tracking the industrial growth of modern China with high-resolution
panchromatic imagery: A sequential convolutional approach
January 23, 2023
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Computer Science
Computer Vision and Pattern Recognition
Computers and Society
Machine Learning
Due to insufficient or difficult to obtain data on development in
inaccessible regions, remote sensing data is an important tool for interested
stakeholders to collect information on economic growth. To date, no studies
have utilized deep l...