6 citations · 7 across the 3 of their papers we have counts for
4 papers
LLM-Guided Ansätze Design for Quantum Circuit Born Machines in Financial Generative Modeling
Yaswitha Gujju, Romain Harang, Tetsuo Shibuya
Quantum generative modeling using quantum circuit Born machines (QCBMs) shows promising potential for practical quantum advantage. However, discovering ansätze that are both expres…
Tracking World States with Language Models: State-Based Evaluation Using Chess
Romain Harang, Jason Naradowsky, Yaswitha Gujju +1
Large Language Models (LLMs) exhibit emergent capabilities in structured domains, suggesting they may implicitly internalize high-fidelity representations of world models. While pr…
QuProFS: An Evolutionary Training-free Approach to Efficient Quantum Feature Map Search
Yaswitha Gujju, Romain Harang, Chao Li +2
The quest for effective quantum feature maps for data encoding presents significant challenges, particularly due to the flat training landscapes and lengthy training processes asso…
Quantum Machine Learning on Near-Term Quantum Devices: Current State of Supervised and Unsupervised Techniques for Real-World Applications
Yaswitha Gujju, Atsushi Matsuo, Rudy Raymond
The past decade has witnessed significant advancements in quantum hardware, encompassing improvements in speed, qubit quantity, and quantum volume-a metric defining the maximum siz…