Quantum Machine Learning
290 papers from Europe PMC
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 145-156 of 290
Universal terminal for cloud quantum computing.
Khazali M.
Unleashing quantum algorithms with Qinterpreter: bridging the gap between theory and practice across leading quantum computing platforms.
Contreras-Sepúlveda W, Villegas-Martínez BM, Gesing S, Sánchez-Mondragón JJ, Sánchez-Pérez JC, Vidales-Basurto CA, Escobedo-Alatorre JJ, Torres-Palencia AD, Palillero-Sandoval O, Licea-Rodriguez J, Lozano-Crisóstomo N, García-Melgarejo JC, Palacios-Perez EN.
Advances in Quantum Computing.
La Cour B.
Deep Neural Network Assisted Quantum Chemistry Calculations on Quantum Computers.
Ghosh K, Kumar S, Rajan NM, Yamijala SSRKC.
Enhancing the performance of an open quantum battery by adjusting its velocity
Mojaveri B, Bahrbeig RJ, Fasihi MA, Babanzadeh S.
Enhancing the Security of the BB84 Quantum Key Distribution Protocol against Detector-Blinding Attacks via the Use of an Active Quantum Entropy Source in the Receiving Station.
Stipčević M.
Fast reconstruction algorithm based on HMC sampling.
Lian H, Xu J, Zhu Y, Fan Z, Liu Y, Shan Z.
Investigating Imperfect Cloning for Extending Quantum Communication Capabilities.
Iqbal M, Velasco L, Costa N, Napoli A, Pedro J, Ruiz M.
Non-Markovian cost function for quantum error mitigation with Dirac Gamma matrices representation.
Ahn D.
Optimizing quantum noise-induced reservoir computing for nonlinear and chaotic time series prediction.
Fry D, Deshmukh A, Chen SY, Rastunkov V, Markov V.
Q-Pandora Unboxed: Characterizing Noise Resilience of Quantum Error Correction Codes
Chatterjee A, Das S, Ghosh S.
Quantum neural networks with multi-qubit potentials.
Ban Y, Torrontegui E, Casanova J.