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 253-264 of 521
Modelling Quantum Software
Luis Mariano Bibbo, Alejandro Fernandez, José Manuel Suarez, Oscar Pastor
Modular quantum extreme reservoir computing
Hon Wai Lau, Aoi Hayashi, Akitada Sakurai, William John Munro, Kae Nemoto
Molecular Modeling of Self-Assembling Peptides.
Jones SJ, Perez A
Monolithically Integrated Ultra-Low Noise Balanced Receiver for CV-QKD
Dinka Milovančev, Nemanja Vokić
Multi-party quantum Byzantine consensus based on full quantum one-way function
Tao Shang, Yao Tang, Yuanjing Zhang, Kun Zhang, Yazhuo Jiang
Multidimensional compressed sensing to advance (23) Na multi-quantum coherences MRI.
Licht C, Reichert S, Guye M, Schad LR, Rapacchi S
Multifaceted Analysis of Intermolecular Interactions in α-Terpineol-Halobenzenes Binary Mixtures: Insights from Thermophysical, Acoustical, and Spectral Techniques, Supported by Quantum Computational Approaches
Unknown
Multimodal Quantum Natural Language Processing: A Novel Framework for using Quantum Methods to Analyse Real Data
Hala Hawashin
Multiscale chemogenetic dissection of fronto-temporal top-down regulation for object memory in primates
Toshiyuki Hirabayashi, Yuji Nagai, Yuki Hori, Yukiko Hori, Kei Oyama, Koki Mimura, Naohisa Miyakawa, Haruhiko Iwaoki, Ken-ichi Inoue, Tetsuya Suhara, Masahiko Takada, Makoto Higuchi, Takafumi Minamimoto
NAC-QFL: Noise Aware Clustered Quantum Federated Learning
Himanshu Sahu, Hari Prabhat Gupta
Natural gradient and parameter estimation for quantum Boltzmann machines
Dhrumil Patel, Mark M. Wilde
Neural Network Matrix Product Operator: A Multi-Dimensionally Integrable Machine Learning Potential
Kentaro Hino, Yuki Kurashige