Superconducting quantum computing: a review

HL Huang, D Wu, D Fan, X Zhu - Science China Information Sciences, 2020 - Springer
Over the last two decades, tremendous advances have been made for constructing large-
scale quantum computers. In particular, quantum computing platforms based on …

A machine learning approach to Bayesian parameter estimation

S Nolan, A Smerzi, L Pezzè - npj Quantum Information, 2021 - nature.com
Bayesian estimation is a powerful theoretical paradigm for the operation of the approach to
parameter estimation. However, the Bayesian method for statistical inference generally …

Quantum Artificial Intelligence: A Brief Survey

M Klusch, J Lässig, D Müssig, A Macaluso… - KI-Künstliche …, 2024 - Springer
Abstract Quantum Artificial Intelligence (QAI) is the intersection of quantum computing and
AI, a technological synergy with expected significant benefits for both. In this paper, we …

An Optimal, Power Efficient, Internet of Medical Things Framework for Monitoring of Physiological Data Using Regression Models

A Mishra, LS Liberman, N Brahamanpally - Sensors, 2024 - mdpi.com
The sensors used in the Internet of Medical Things (IoMT) network run on batteries and need
to be replaced, replenished or should use energy harvesting for continuous power needs …

A reformulation of additive models

A Wozniakowski - 2022 - dr.ntu.edu.sg
Additive models and their fitting algorithms play a pivotal role in the history and development
of applied mathematics, machine learning, statistics, and science. Yet, the traditional …

Pipeline API

S API - scikit-physlearn.readthedocs.io
Pipeline API — Scikit-physlearn 0.1.8 documentation Navigation index modules | next |
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