Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
Large-scale quantum reservoir learning with an analog quantum computer
Quantum machine learning has gained considerable attention as quantum technology
advances, presenting a promising approach for efficiently learning complex data patterns …
advances, presenting a promising approach for efficiently learning complex data patterns …
Hybrid Quantum Deep Learning With Superpixel Encoding for Earth Observation Data Classification
Earth observation (EO) has inevitably entered the Big Data era. The computational
challenge associated with analyzing large EO data using sophisticated deep learning …
challenge associated with analyzing large EO data using sophisticated deep learning …
Quantum Hamiltonian Embedding of Images for Data Reuploading Classifiers
When applying quantum computing to machine learning tasks, one of the first considerations
is the design of the quantum machine learning model itself. Conventionally, the design of …
is the design of the quantum machine learning model itself. Conventionally, the design of …
Can Geometric Quantum Machine Learning Lead to Advantage in Barcode Classification?
We consider the problem of distinguishing two vectors (visualized as images or barcodes)
and learning if they are related to one another. For this, we develop a geometric quantum …
and learning if they are related to one another. For this, we develop a geometric quantum …
Quantum Computing for Automotive Applications: From Algorithms to Applications
Quantum computing could impact various industries, with the automotive industry with many
computational challenges, from optimizing supply chains and manufacturing to vehicle …
computational challenges, from optimizing supply chains and manufacturing to vehicle …
Patch-Based End-to-End Quantum Learning Network for Reduction and Classification of Classical Data
In the noisy intermediate scale quantum (NISQ) era, the control over the qubits is limited due
to the errors caused by quantum decoherence, crosstalk, and imperfect calibration. Hence, it …
to the errors caused by quantum decoherence, crosstalk, and imperfect calibration. Hence, it …
[PDF][PDF] Quantum Computing for Automotive Applications: From Algorithms to Applications
LH Kiwit, M Erdmann, L Müller, C Kumar, YA Berrada… - researchgate.net
Quantum computing could impact various industries, with the automotive industry with many
computational challenges, from optimizing supply chains and manufacturing to vehicle …
computational challenges, from optimizing supply chains and manufacturing to vehicle …
Audio classification using quantum techniques
A Majumder - 2024 - dspace.bracu.ac.bd
Quantum computing is a new type of computing system that is rapidly emerging with
immense success in the area of computer science. In our day-to-day lives, there are different …
immense success in the area of computer science. In our day-to-day lives, there are different …