1 citations · 1 across the 6 of their papers we have counts for
6 papers
Hybrid quantum-classical neural network for sentiment analysis
Giacomo Cappiello, Filippo Caruso, Xing Liang +1
Quantum machine learning has recently emerged as a promising paradigm that leverages the expressive power of quantum circuits to address complex learning tasks. In this work, we in…
Spectral Geometry and Bosonic-Bloch Probes: Explorations in Quantum Learning
Santanu Ganguly, Xing Liang, Dimitrios Makris
This paper studies how spectral geometry emerges in quantum learning models and how it can be diagnosed with physically grounded probes. In graph-regularized quantum networks, trai…
Quantum Generative Diffusion Model for Real-World Time Series
Jack Waller, Filippo Caruso, Dimitrios Makris +2
Generative models have achieved remarkable success in data synthesis, though recent advances driven by increasing model scale have introduced challenges in computational cost and e…
Compression-Driven Anomaly Detection in Brain MRI Using an Interpretable Quantum Autoencoder
Santanu Ganguly, Xing Liang, Dimitrios Makris
We study a quantum autoencoder (QAE) for compression-driven anomaly detection in brain MRI data. The approach leverages angle encoding to map image patches into quantum states, fol…
Solving larger Travelling Salesman Problem networks with a penalty-free Variational Quantum Algorithm
Daniel Goldsmith, Xing Liang, Dimitrios Makris +1
The Travelling Salesman Problem (TSP) is a well-known NP-hard combinatorial optimisation problem with important industrial applications. Although extensively studied, quantum solut…
Locality-aware Qubit Routing for the Grid Architecture
Avah Banerjee, Xin Liang, Rod Tohid
Due to the short decohorence time of qubits available in the NISQ-era, it is essential to pack (minimize the size and or the depth of) a logical quantum circuit as efficiently as p…