From the 1 of 5 linked papers with an AI index.
5 papers
Benchmarking loss functions for trainable quantum feature maps
Nguyen Dinh Quyen, Vu Tuan Hai, Quoc Chuong Nguyen +2
The paper evaluates how different loss functions affect the training of quantum feature maps used in quantum machine learning, finding that Log-Likelihood Loss offers stable optimi…
Quantum resource reduction for quantum-centric supercomputing via correlated mean-field downfolding framework
Thien Ngoc Tran, Lan Nguyen Tran
We present OBDF-SQD, a hybrid quantum-classical method that combines one-body downfolding~(OBDF) based on one-body Møller--Plesset second-order perturbation theory (OBMP2) with sa…
Towards Automated Selection of Quantum Encoding Circuits via Meta-Learning
Dao Duy Tung, Nguyen Quoc Chuong, Vu Tuan Hai +2
In recent years, quantum kernel methods have shown promising applications on near-term quantum devices. However, selecting an appropriate encoding circuit for a given dataset requi…
Feedback-Based Quantum Control for Safe and Synergistic Drug Combination Design
Mai Nguyen Phuong Nhi, Lan Nguyen Tran, Le Bin Ho
Drug-drug interactions (DDIs) strongly affect the safety and efficacy of combination therapies. Despite the availability of large DDI databases, selecting optimal multi-drug combin…
Imaginary-time-enhanced feedback-based quantum algorithms for universal ground-state preparation
Thanh Nguyen Van Long, Lan Nguyen Tran, Le Bin Ho
Preparing ground states of strongly correlated quantum systems is a central goal in quantum simulation and optimization. The feedback-based quantum algorithm (FALQON) provides an a…