Quantum Machine Learning
521 papers for year 2024
Quantum Machine Learning Research Context
This category covers quantum machine learning research, including quantum kernels, variational classifiers, hybrid learning systems, generative models, and QML benchmarks.
Showing 205-216 of 521
Improving student understanding of the number of distinct many-particle states for a system of identical particles with a fixed number of available single-particle states
Christof Keebaugh, Emily Marshman, Chandralekha Singh
In Search of Quantum Advantage: Estimating the Number of Shots in Quantum Kernel Methods
Artur Miroszewski, Marco Fellous Asiani, Jakub Mielczarek, Bertrand Le Saux, Jakub Nalepa
India's Quantum Technology Advancements: National Security Implications for Pakistan
Zohaib Altaf, Nimra Javed
Information plane and compression-gnostic feedback in quantum machine learning
Nathan Haboury, Mo Kordzanganeh, Alexey Melnikov, Pavel Sekatski
INNOVATIVE MECHANISMS FOR IMPLEMENTING STATE ECONOMIC POLICY FOR POST-WAR RECONSTRUCTION OF UKRAINE: QUANTUM TRANSFORMATIONS AS A DRIVER OF DEVELOPMENT
Oleksiy Shkuratov, Liudmila Antonova, Roman Dzyuba
Integrated Encoding and Quantization to Enhance Quanvolutional Neural Networks
Daniele Lizzio Bosco, Beatrice Portelli, Giuseppe Serra
Interactive Learning Media Utilizing Google Sites on Quantum Mechanics Topic
Aris Kurniawan, Rida SN Mahmudah, Rifkiyatul Khairiyah, Putri Dinda Alfadia Lestari
INTERDISCIPLINARY APPROACH WITH S.M.A.R.T. MANAGEMENT ADVOCATING HIGHER-ORDER THINKING IN PRIMARY SCHOOL STUDENTS
BALACHANDRAN ANNAMALAI, TIRZAH ZUBEIDAH ZACHARIAH
Introducing GPU-acceleration into the Python-based Simulations of Chemistry Framework
Rui Li, Qiming Sun, Xing Zhang, Garnet Kin-Lic Chan
Investigate the Performance of Distribution Loading with Conditional Quantum Generative Adversarial Network Algorithm on Quantum Hardware with Error Suppression
Anh Pham, Andrew Vlasic
Investigating and Mitigating Barren Plateaus in Variational Quantum Circuits: A Survey
Jack Cunningham, Jun Zhuang
Investigating layer-selective transfer learning of QAOA parameters for Max-Cut problem
Francesco Aldo Venturelli, Sreetama Das, Filippo Caruso