
Entangled Datasets for Quantum Machine Learning
Highquality, largescale datasets have played a crucial role in the dev...
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Adaptive Machine Learning for TimeVarying Systems: Low Dimensional Latent Space Tuning
Machine learning (ML) tools such as encoderdecoder convolutional neural...
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Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis
We present a method for learning "spectrally descriptive" edge weights f...
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Unsupervised Learning of FullWaveform Inversion: Connecting CNN and Partial Differential Equation in a Loop
This paper investigates unsupervised learning of FullWaveform Inversion...
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Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra
Constructing probability densities for inference in highdimensional spe...
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CoarseGrain Cluster Analysis of Tensors With Application to Climate Biome Identification
A tensor provides a concise way to codify the interdependence of complex...
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AIM 2020 Challenge on Real Image SuperResolution: Methods and Results
This paper introduces the real image SuperResolution (SR) challenge tha...
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A deep QLearning based Path Planning and Navigation System for Firefighting Environments
Live fire creates a dynamic, rapidly changing environment that presents ...
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Does Phase Matter For Monaural Source Separation?
The "cocktail party" problem of fully separating multiple sources from a...
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Belief Propagation MinSum Algorithm for Generalized MinCost Network Flow
Belief Propagation algorithms are instruments used broadly to solve grap...
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Efficient DataDriven Geologic Feature Detection from Prestack Seismic Measurements using Randomized MachineLearning Algorithm
Conventional seismic techniques for detecting the subsurface geologic fe...
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Hierarchical modeling of molecular energies using a deep neural network
We introduce the Hierarchically Interacting Particle Neural Network (HIP...
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A New Spectral Clustering Algorithm
We present a new clustering algorithm that is based on searching for nat...
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Convolutional Dictionary Learning
Convolutional sparse representations are a form of sparse representation...
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Machine learning for graphbased representations of threedimensional discrete fracture networks
Structural and topological information play a key role in modeling of fl...
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Gauging Variational Inference
Computing partition function is the most important statistical inference...
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Aggressive Sampling for Multiclass to Binary Reduction with Applications to Text Classification
We address the problem of multiclass classification in the case where t...
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Extremal Optimization for Graph Partitioning
Extremal optimization is a new generalpurpose method for approximating ...
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Optimization with Extremal Dynamics
We explore a new generalpurpose heuristic for finding highquality solu...
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Reconstructing parameters of spreading models from partial observations
Spreading processes are often modelled as a stochastic dynamics occurrin...
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Minimum Weight Perfect Matching via Blossom Belief Propagation
Maxproduct Belief Propagation (BP) is a popular messagepassing algorit...
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MCMC assisted by Belief Propagaion
Markov Chain Monte Carlo (MCMC) and Belief Propagation (BP) are the most...
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Efficient reconstruction of transmission probabilities in a spreading process from partial observations
An important problem of reconstruction of diffusion network and transmis...
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Loop Calculus and BootstrapBelief Propagation for Perfect Matchings on Arbitrary Graphs
This manuscript discusses computation of the Partition Function (PF) and...
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Belief Propagation for Linear Programming
Belief Propagation (BP) is a popular, distributed heuristic for performi...
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Quantifying Uncertainty in Stochastic Models with Parametric Variability
We present a method to quantify uncertainty in the predictions made by s...
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When is social computation better than the sum of its parts?
Social computation, whether in the form of searches performed by swarms ...
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The Dilated Triple
The basic unit of meaning on the Semantic Web is the RDF statement, or t...
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A Reflection on the Structure and Process of the Web of Data
The Web community has introduced a set of standards and technologies for...
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Interpretations of the Web of Data
The emerging Web of Data utilizes the web infrastructure to represent an...
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Faith in the Algorithm, Part 2: Computational Eudaemonics
Eudaemonics is the study of the nature, causes, and conditions of human ...
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Robust Compressed Sensing and Sparse Coding with the Difference Map
In compressed sensing, we wish to reconstruct a sparse signal x from obs...
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Learning from dependent observations
In most papers establishing consistency for learning algorithms it is as...
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Automatic creation of urban velocity fields from aerial video
In this paper, we present a system for modelling vehicle motion in an ur...
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Camera distortion selfcalibration using the plumbline constraint and minimal Hough entropy
In this paper we present a simple and robust method for selfcorrection ...
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Faster and better: a machine learning approach to corner detection
The repeatability and efficiency of a corner detector determines how lik...
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The EulerPoincare theory of Metamorphosis
In the pattern matching approach to imaging science, the process of "met...
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Spectral Methods in the Presence of Discontinuities
Spectral methods provide an elegant and efficient way of numerically sol...
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DockerEnabled Build and Execution Environment (BEE): an Encapsulated Environment Enabling HPC Applications Running Everywhere
Variations in High Performance Computing (HPC) system software configura...
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A Grateful Dead Analysis: The Relationship Between Concert and Listening Behavior
The Grateful Dead were an American band that was born out of the San Fra...
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Between conjecture and memento: shaping a collective emotional perception of the future
Large scale surveys of public mood are costly and often impractical to p...
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On the relationship between the structural and socioacademic communities of a coauthorship network
This article presents a study that compares detected structural communit...
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Mapping the Bid Behavior of Conference Referees
The peerreview process, in its present form, has been repeatedly critic...
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Methodology for Multistage, Operations and UncertaintyAware Placement and Sizing of FACTS Devices in a Large Power Transmission System
We develop new optimization methodology for planning installation of Fle...
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Verification Studies for the Noh Problem using Nonideal Equations of State and Finite Strength Shocks
The Noh verification test problem is extended beyond the commonly studie...
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Tools for improving resilience of electric distribution systems with networked microgrids
In the electrical grid, the distribution system is themost vulnerable to...
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Complex Number Formulation and Convex Relaxations for Aircraft Conflict Resolution
We present a novel complex number formulation along with tight convex re...
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Discovering Scholarly Orphans Using ORCID
Archival efforts such as (C)LOCKSS and Portico are in place to ensure th...
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Impact of URI Canonicalization on Memento Count
Quantifying the captures of a URI over time is useful for researchers to...
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Topology Estimation using Graphical Models in MultiPhase Power Distribution Grids
Distribution grid is the medium and low voltage part of a large power sy...
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Los Alamos National Laboratory
Los Alamos National Laboratory is a United States Department of Energy national laboratory initially organized during World War II for the design of nuclear weapons as part of the Manhattan Project.