5 papers
Quantum-Inspired Trainable and Parameter-Efficient Tensor Networks for Image Inpainting
Shiwen An, Konstantinos Slavakis
This work introduces quantum-inspired tensor-network circuits as trainable transforms for image inpainting. Among the proposed architectures, the diagonal quantum Fourier transform…
Fast Trainable Multilinear Bases for Image Compression
Shiwen An, Zhongyi Ni, Huanhai Zhou +1
The Discrete Fourier Transform (DFT), the Discrete Cosine Transform (DCT), and their block-wise variants underpin most deployed image and video codecs. Their effectiveness rests on…
Problem Reductions at Scale: Agentic Integration of Computationally Hard Problems
Xi-Wei Pan, Shi-Wen An, Jin-Guo Liu
Solving an NP-hard optimization problem often requires reformulating it for a specific solver -- quantum hardware, a commercial optimizer, or a domain heuristic. A tool for polynom…
LogosQ: A High-Performance and Type-Safe Quantum Computing Library in Rust
Shiwen An, Jiayi Wang, Konstantinos Slavakis
Developing robust and high performance quantum software is challenging due to the dynamic nature of existing Python-based frameworks, which often suffer from runtime errors and sca…
Tensor-Based Binary Graph Encoding for Variational Quantum Classifiers
Shiwen An, Konstantinos Slavakis
Quantum computing has been a prominent research area for decades, inspiring transformative fields such as quantum simulation, quantum teleportation, and quantum machine learning (Q…