142 citations · 284 across the 14 of their papers we have counts for
15 papers
Trainable Discrete Feature Embeddings for Variational Quantum Classifier
Napat Thumwanit, Chayaphol Lortaraprasert, Hiroshi Yano +1
Quantum classifiers provide sophisticated embeddings of input data in Hilbert space promising quantum advantage. The advantage stems from quantum feature maps encoding the inputs i…
Efficient Construction of Functional Representations for Quantum Algorithms
Lukas Burgholzer, Rudy Raymond, Indranil Sengupta +1
Due to the significant progress made in the implementation of quantum hardware, efficient methods and tools to design corresponding algorithms become increasingly important. Many o…
Detecting Temporal Correlation via Quantum Random Number Generation
Yutaka Shikano, Kentaro Tamura, Rudy Raymond
All computing devices, including quantum computers, must exhibit that for a given input, an output is produced in accordance with the program. The outputs generated by quantum comp…
Optimization of Quantum Circuit Mapping using Gate Transformation and Commutation
Toshinari Itoko, Rudy Raymond, Takashi Imamichi +1
This paper addresses quantum circuit mapping for Noisy Intermediate-Scale Quantum (NISQ) computers. Since NISQ computers constraint two-qubit operations on limited couplings, an in…
Profile-guided memory optimization for deep neural networks
Taro Sekiyama, Takashi Imamichi, Haruki Imai +1
Recent years have seen deep neural networks (DNNs) becoming wider and deeper to achieve better performance in many applications of AI. Such DNNs however require huge amounts of mem…
Dynamic Boltzmann Machines for Second Order Moments and Generalized Gaussian Distributions
Rudy Raymond, Takayuki Osogami, Sakyasingha Dasgupta
Dynamic Boltzmann Machine (DyBM) has been shown highly efficient to predict time-series data. Gaussian DyBM is a DyBM that assumes the predicted data is generated by a Gaussian dis…