On the interpretability of quantum neural networks

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: On the interpretability of quantum neural networks ; volume:6 ; number:2 ; day:28 ; month:8 ; year:2024 ; pages:1-11 ; date:12.2024
Quantum machine intelligence ; 6, Heft 2 (28.8.2024), 1-11, 12.2024

Creator: Pira, Lirandë
Ferrie, Chris

Contributor: SpringerLink (Online service)

DOI: 10.1007/s42484-024-00191-y

URN: urn:nbn:de:101:1-2411132132597.542044538134

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:33 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Show original at data provider

Associated

Pira, Lirandë
Ferrie, Chris
SpringerLink (Online service)

Other Objects (12)

Reliable interpretability of biology-inspired deep neural networks

Transparency and interpretability for learned representations of artificial neural networks

Quantum neural networks

Radial basis function networks for convolutional neural networks to learn similarity distance metric and improve interpretability

Quantum optimization for training quantum neural networks

Quantum activation functions for quantum neural networks

Training deep quantum neural networks

Universal discriminative quantum neural networks

Improving interpretability via regularization of neural activation sensitivity

Regressions on quantum neural networks at maximal expressivity

Layerwise learning for quantum neural networks

Quantifying scrambling in quantum neural networks

Reliable interpretability of biology-inspired deep neural networks

Transparency and interpretability for learned representations of artificial neural networks

Quantum neural networks

Radial basis function networks for convolutional neural networks to learn similarity distance metric and improve interpretability

Quantum optimization for training quantum neural networks

Quantum activation functions for quantum neural networks

Training deep quantum neural networks

Universal discriminative quantum neural networks

Improving interpretability via regularization of neural activation sensitivity

Regressions on quantum neural networks at maximal expressivity

Layerwise learning for quantum neural networks

Quantifying scrambling in quantum neural networks

Reliable interpretability of biology-inspired deep neural networks

Transparency and interpretability for learned representations of artificial neural networks

Quantum neural networks

Radial basis function networks for convolutional neural networks to learn similarity distance metric and improve interpretability

Quantum optimization for training quantum neural networks

Quantum activation functions for quantum neural networks

Training deep quantum neural networks

Universal discriminative quantum neural networks

Improving interpretability via regularization of neural activation sensitivity

Regressions on quantum neural networks at maximal expressivity

Layerwise learning for quantum neural networks

Quantifying scrambling in quantum neural networks

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.

On the interpretability of quantum neural networks

Object Details

References and Relationships

Contributors, Places and Time

Further information

Data provider

Associated

Other Objects (12)

Reliable interpretability of biology-inspired deep neural networks

Transparency and interpretability for learned representations of artificial neural networks

Quantum neural networks

Radial basis function networks for convolutional neural networks to learn similarity distance metric and improve interpretability

Quantum optimization for training quantum neural networks

Quantum activation functions for quantum neural networks

Training deep quantum neural networks

Universal discriminative quantum neural networks

Improving interpretability via regularization of neural activation sensitivity

Regressions on quantum neural networks at maximal expressivity

Layerwise learning for quantum neural networks

Quantifying scrambling in quantum neural networks

Reliable interpretability of biology-inspired deep neural networks

Transparency and interpretability for learned representations of artificial neural networks

Quantum neural networks

Radial basis function networks for convolutional neural networks to learn similarity distance metric and improve interpretability

Quantum optimization for training quantum neural networks

Quantum activation functions for quantum neural networks

Training deep quantum neural networks

Universal discriminative quantum neural networks

Improving interpretability via regularization of neural activation sensitivity

Regressions on quantum neural networks at maximal expressivity

Layerwise learning for quantum neural networks

Quantifying scrambling in quantum neural networks

Reliable interpretability of biology-inspired deep neural networks

Transparency and interpretability for learned representations of artificial neural networks

Quantum neural networks

Radial basis function networks for convolutional neural networks to learn similarity distance metric and improve interpretability

Quantum optimization for training quantum neural networks

Quantum activation functions for quantum neural networks

Training deep quantum neural networks

Universal discriminative quantum neural networks

Improving interpretability via regularization of neural activation sensitivity

Regressions on quantum neural networks at maximal expressivity

Layerwise learning for quantum neural networks

Quantifying scrambling in quantum neural networks

Related objects

Reset password