35 citations · 42 across the 16 of their papers we have counts for
5 papers · 1 filter
Accelerating Inference for Multilayer Neural Networks with Quantum Computers
Arthur G. Rattew, Po-Wei Huang, Naixu Guo +2
Fault-tolerant Quantum Processing Units (QPUs) promise to deliver exponential speed-ups in select computational tasks, yet their integration into modern deep learning pipelines rem…
Quantum Learning with Tunable Loss Functions
Yixian Qiu, Lirandë Pira, Patrick Rebentrost
Learning from quantum data presents new challenges to the paradigm of learning from data. This typically entails the use of quantum learning models to learn quantum processes that…
Expressivity Limits in Quantum Walk-based Optimization
Guilherme A. Bridi, Debbie Lim, Lirandë Pira +3
Quantum algorithms have emerged as a promising tool to solve combinatorial optimization problems. The quantum walk optimization algorithm (QWOA) is one such variational approach th…
Degree-Optimized Cumulative Polynomial Kolmogorov-Arnold Networks
Mathew Vanherreweghe, Lirandë Pira, Patrick Rebentrost
We introduce cumulative polynomial Kolmogorov-Arnold networks (CP-KAN), a neural architecture combining Chebyshev polynomial basis functions and quadratic unconstrained binary opti…
Enhanced Photonic Chip Design via Interpretable Machine Learning Techniques
Lirandë Pira, Airin Antony, Nayanthara Prathap +2
Photonic chip design has seen significant advancements with the adoption of inverse design methodologies, offering flexibility and efficiency in optimizing device performance. Howe…