Results 61 to 70 of about 9,085,112 (391)
Barren plateaus in quantum neural network training landscapes [PDF]
Nature Communications, 2018 Many experimental proposals for noisy intermediate scale quantum devices involve training a parameterized quantum circuit with a classical optimization loop.
J. McClean +4 more
semanticscholar +1 more source
A new adaptive neural network and heuristics hybrid approach for job-shop scheduling [PDF]
, 2001 Copyright @ 2001 Elsevier Science LtdA new adaptive neural network and heuristics hybrid approach for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving the ...
Baker +18 more
core +2 more sources
Neural Networks, 2003 In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large
CIARAMELLA A. +12 more
openaire +6 more sources
Boosting Neural Networks [PDF]
Neural Computation, 2000 Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, Ada Boost, has been applied with great success to several benchmark machine learning problems using mainly decision trees as base classifiers.
Schwenk, Holger, Bengio, Yoshua
openaire +3 more sources
ICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2020 In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well as the decoder at each destination node, are neural networks which are all trained jointly for the task of communicating correlated sources through a network of noisy point ...
Liu, Litian +3 more
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Spinal Cord Injury in Myelomeningocele: Prospects for Therapy
Frontiers in Cellular Neuroscience, 2020 Myelomeningocele (MMC) is the most common congenital defect of the central nervous system and results in devastating and lifelong disability. In MMC, the initial failure of neural tube closure early in gestation is followed by a progressive prenatal ...
Karolina Janik +3 more
doaj +1 more source
Voltage stability analysis of load buses in electric power system using adaptive neuro-fuzzy inference system (anfis) and probabilistic neural network (pnn) [PDF]
, 2017 This paper presents the application of neural networks for analysing voltage stability of load buses in electric power system. Voltage stability margin (VSM) and load power margin (LPM) are used as the indicators for analysing voltage stability.
Ab Ghani, Ahmad Raqib +4 more
core +1 more source
Performance of neural network basecalling tools for Oxford Nanopore sequencing
Genome Biology, 2019 Basecalling, the computational process of translating raw electrical signal to nucleotide sequence, is of critical importance to the sequencing platforms produced by Oxford Nanopore Technologies (ONT).
R. Wick, L. Judd, K. Holt
semanticscholar +1 more source
The use of adversaries for optimal neural network training [PDF]
, 2018 B-decay data from the Belle experiment at the KEKB collider have a substantial background from $e^{+}e^{-}\to q \bar{q}$ events. To suppress this we employ deep neural network algorithms.
Hawthorne-Gonzalvez, Anton +1 more
core +2 more sources
On the Robustness of a Neural Network [PDF]
2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS), 2017 36th IEEE International Symposium on Reliable Distributed Systems 26 - 29 September 2017.
El Mhamdi, El Mahdi +2 more
openaire +4 more sources