
Machine Learning by TwoDimensional Hierarchical Tensor Networks: A Quantum Information Theoretic Perspective on Deep Architectures
The resemblance between the methods used in studying quantummany body p...
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Quantum Enhanced Inference in Markov Logic Networks
Markov logic networks (MLNs) reconcile two opposing schools in machine l...
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Somoclu: An Efficient Parallel Library for SelfOrganizing Maps
Somoclu is a massively parallel tool for training selforganizing maps o...
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Singleshot Adaptive Measurement for Quantumenhanced Metrology
Quantumenhanced metrology aims to estimate an unknown parameter such th...
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Learning in Quantum Control: HighDimensional Global Optimization for Noisy Quantum Dynamics
Quantum control is valuable for various quantum technologies such as hig...
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Inductive supervised quantum learning
In supervised learning, an inductive learning algorithm extracts general...
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A Physical Metaphor to Study Semantic Drift
In accessibility tests for digital preservation, over time we experience...
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Monitoring Term Drift Based on Semantic Consistency in an Evolving Vector Field
Based on the Aristotelian concept of potentiality vs. actuality allowing...
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Adversarial Domain Adaptation for Identifying Phase Transitions
The identification of phases of matter is a challenging task, especially...
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Anchored Network Users: Stochastic Evolutionary Dynamics of Cognitive Radio Network Selection
To solve the spectrum scarcity problem, the cognitive radio technology i...
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Bayesian Deep Learning on a Quantum Computer
Bayesian methods in machine learning, such as Gaussian processes, have g...
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An Artificial Spiking Quantum Neuron
Artificial spiking neural networks have found applications in areas wher...
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Open source software in quantum computing
Open source software is becoming crucial in the design and testing of qu...
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