Jan Lukas Robertus

Follow

Generating author description...

Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ A Quantum Approximate Optimization Algorithm 2014 Edward Farhi
Jeffrey Goldstone
Sam Gutmann
1
+ On Kernel Target Alignment 2006 Nello Cristianini
Jaz Kandola
André Elisseeff
John Shawe‐Taylor
1
+ PDF Chat Quantum machine learning 2017 Jacob Biamonte
Péter Wittek
Nicola Pancotti
Patrick Rebentrost
Nathan Wiebe
Seth Lloyd
1
+ PDF Chat Quantum Machine Learning in Feature Hilbert Spaces 2019 Maria Schuld
Nathan Killoran
1
+ PDF Chat Supervised learning with quantum-enhanced feature spaces 2019 Vojtěch Havlíček
Antonio Córcoles
Kristan Temme
Aram W. Harrow
Abhinav Kandala
Jerry M. Chow
Jay Gambetta
1
+ Adam: A Method for Stochastic Optimization 2014 Diederik P. Kingma
Jimmy Ba
1
+ PDF Chat Demonstration of quantum advantage in machine learning 2017 Diego Ristè
Marcus P. da Silva
Colm A. Ryan
Andrew W. Cross
Antonio Córcoles
John A. Smolin
Jay Gambetta
Jerry M. Chow
Blake Johnson
1
+ PDF Chat Power of data in quantum machine learning 2021 Hsin-Yuan Huang
Michael Broughton
Masoud Mohseni
Ryan Babbush
Sergio Boixo
Hartmut Neven
Jarrod R. McClean
1
+ PDF Chat Training quantum embedding kernels on near-term quantum computers 2022 Thomas Hubregtsen
David Wierichs
Elies Gil-Fuster
Peter-Jan H. S. Derks
Paul K. Faehrmann
Johannes Jakob Meyer
1
+ PDF Chat A survey on graph-based deep learning for computational histopathology 2021 David Ahmedt‐Aristizabal
Mohammad Ali Armin
Simon Denman
Clinton Fookes
Lars Petersson
1
+ PDF Chat A rigorous and robust quantum speed-up in supervised machine learning 2021 Yunchao Liu
Srinivasan Arunachalam
Kristan Temme
1
+ PDF Chat Application of quantum machine learning using the quantum kernel algorithm on high energy physics analysis at the LHC 2021 S. L. Wu
S. Sun
W. Guan
C. Zhou
J. Chan
Chi Lung Cheng
Tuan Q. Pham
Yan Qian
Alex Zeng Wang
R. Zhang
1
+ Hierarchical graph representations in digital pathology 2021 Pushpak Pati
Guillaume Jaume
Antonio Foncubierta–Rodríguez
Florinda Feroce
Anna Maria Anniciello
Giosuè Scognamiglio
Nadia Brancati
Maryse Fiche
Estelle Dubruc
Daniel Riccio
1
+ Bandwidth Enables Generalization in Quantum Kernel Models 2022 Abdülkadir Canatar
Evan Peters
Cengiz Pehlevan
Stefan M. Wild
Ruslan Shaydulin
1
+ PDF Chat Challenges and opportunities in quantum machine learning 2022 M. Cerezo
Guillaume Verdon
Hsin-Yuan Huang
Łukasz Cincio
Patrick J. Coles
1
+ Algorithms for Learning Kernels Based on Centered Alignment 2012 Corinna Cortes
Mehryar Mohri
Afshin Rostamizadeh
1
+ Importance of kernel bandwidth in quantum machine learning 2022 Ruslan Shaydulin
Stefan M. Wild
1
+ PDF Chat Quantum machine learning framework for virtual screening in drug discovery: a prospective quantum advantage 2023 Stefano Mensa
Emre Sahin
Francesco Tacchino
Panagiotis Kl. Barkoutsos
Ivano Tavernelli
1
+ PDF Chat Quantum Phase Recognition via Quantum Kernel Methods 2023 Yusen Wu
Bujiao Wu
Jingbo Wang
Xiao Yuan
1
+ PDF Chat Quantum Kernel Alignment with Stochastic Gradient Descent 2023 Gian Gentinetta
David Sutter
Christa Zoufal
Bryce Fuller
Stefan Woerner
1
+ Quantum Multiple Kernel Learning in Financial Classification Tasks 2023 Shungo Miyabe
Brian Quanz
Noriaki Shimada
Abhijit Mitra
Takahiro Yamamoto
Vladimir Rastunkov
Dimitris Alevras
Mekena Metcalf
D.J.M. King
Mohammad Mamouei
1
+ PDF Chat Quantum computing with Qiskit 2024 Ali Javadi-Abhari
Matthew Treinish
Kevin Krsulich
Christopher J. Wood
Jake Lishman
Julien Gacon
Simon Martiel
Paul D. Nation
Lev S. Bishop
Andrew W. Cross
1