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Managing the response to natural disasters effectively can considerably mitigate their devastating impact.
A note on two problems in connexion with graphs
E. W. Dijkstra · 1959
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Experiments with the Graph Traverser program
J. E. Doran and D. Michie · 1966
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Combinatorial Optimization: What Is the State of the Art
Victor Klee · 1980
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Natural gradient works efficiently in learning
Shun-Ichi Amari · 1998
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Prognostic estimations of casualties caused by strong seismic impacts
Jose Badal and E Samardzhieva · 2002
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Shortest paths on dynamic graphs
Giacomo Nannicini and Leo Liberti · 2008
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Estimating casualties for large earthquakes worldwide using an empirical approach
Kishor Jaiswal, David J Wald, and Mike Hearne · 2009
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Shortest Path Algorithm within Dynamic Restricted Searching Area in City Emergency Rescue
Fanliang Bu and Hui Fang · 2010
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Interacting quantum observables: categorical algebra and diagrammatics
Bob Coecke and Ross Duncan · 2011
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An evaluation method for the urban post-earthquake fire risk considering multiple scenarios of fire spread and evacuation
Tomoaki Nishino, Takeyoshi Tanaka, and Akihiko Hokugo · 2012
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Path Optimization Study for Vehicles Evacuation based on Dijkstra Algorithm
Yi-zhou Chen, Shi-fei Shen, Tao Chen, and Rui Yang · 2014
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The Utilisation of Dijkstra’s Algorithm to Assist Evacuation Route in Higher and Close Building
Nor Amalina Mohd Sabri, Abd Samad Hasan Basari, Burairah Husin, and Khyrina Airin Fariza Abu Samah · 2015
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A Dijkstra-Based Algorithm for Selecting the Shortest-Safe Evacuation Routes in Dynamic Environments
Angely Oyola, Dennis G. Romero, and Boris X. Vintimilla · 2017
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Quantum machine learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
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OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks
Geoff Boeing · 2017
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A tutorial on fisher information, 2017
Alexander Ly, Maarten Marsman, Josine Verhagen, Raoul Grasman, and Eric-Jan Wagenmakers · 2017
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Deep learning for accelerated seismic reliability analysis of transportation networks
Mohammad Amin Nabian and Hadi Meidani · 2018
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Machine learning & artificial intelligence in the quantum domain: a review of recent progress
Vedran Dunjko and Hans J Briegel · 2018
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FiLM: Visual Reasoning with a General Conditioning Layer
Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, and Aaron Courville · 2018
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An analysis method on post-earthquake traversability of road network considering building collapse
Zhen XU, Wei Jin, and Ming Zheng · 2019
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Effect of spatial variability of earthquake ground motions on the reliability of road system
Pinom Ering and GL Sivakumar Babu · 2020
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Application of open tools and datasets to probabilistic modeling of road traffic disruptions due to earthquake damage
Catarina Costa, Rui Figueiredo, Vitor Silva, and Paolo Bazzurro · 2020
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Challenges and opportunities in quantum machine learning
M. Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, and Patrick J. Coles · 2022
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Practical application-specific advantage through hybrid quantum computing
Michael Perelshtein, Asel Sagingalieva, Karan Pinto, Vishal Shete, Alexey Pakhomchik, et al · 2022
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Hyperparameter optimization of hybrid quantum neural networks for car classification
Asel Sagingalieva, Andrii Kurkin, Artem Melnikov, Daniil Kuhmistrov, et al · 2022
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OpenQASM 3: A broader and deeper quantum assembly language
Andrew Cross, Ali Javadi-Abhari, Thomas Alexander, Niel de Beaudrap, Lev S. Bishop, et al · 2022
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Quantum machine learning: from physics to software engineering
Alexey Melnikov, Mohammad Kordzanganeh, Alexander Alodjants, and Ray-Kuang Lee · 2023
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Adrián Pérez-Salinas, Alba Cervera-Lierta, Elies Gil-Fuster, and José I. Latorre · 2020
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ZX-calculus for the working quantum computer scientist
John van de Wetering · 2020
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Effect of data encoding on the expressive power of variational quantum-machine-learning models
Maria Schuld, Ryan Sweke, and Johannes Jakob Meyer · 2021
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Quantum Machine Learning for Radio Astronomy
Mohammad Kordzanganeh, Aydin Utting, and Anna Scaife · 2021
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The power of quantum neural networks
Amira Abbas, David Sutter, Christa Zoufal, Aurélien Lucchi, Alessio Figalli, et al · 2021
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Fisher information universally identifies quantum resources
Kok Chuan Tan, Varun Narasimhachar, and Bartosz Regula · 2021
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A Deep Learning Approach for Network-wide Dynamic Traffic Prediction during Hurricane Evacuation
Rezaur Rahman and Samiul Hasan · 2022
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Hybrid quantum neural network for drug response prediction
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Quantum algorithms applied to satellite mission planning for Earth observation
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Quantum machine learning for image classification
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Forecasting the steam mass flow in a powerplant using the parallel hybrid network
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Parallel Hybrid Networks: an interplay between quantum and classical neural networks
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pennylane.templates.layers.basic_entangler — PennyLane
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Completeness of the ZX-calculus
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An exponentially-growing family of universal quantum circuits
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Exponential data encoding for quantum supervised learning
S. Shin, Y. S. Teo, and H. Jeong · 2023
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