Search Results for author: Rudy Raymond

Found 8 papers, 3 papers with code

Quantum Machine Learning on Near-Term Quantum Devices: Current State of Supervised and Unsupervised Techniques for Real-World Applications

no code implementations3 Jul 2023 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 size of a quantum circuit effectively implementable on near-term quantum devices.

Quantum Machine Learning

Decentralized Collaborative Learning with Probabilistic Data Protection

no code implementations23 Aug 2022 Tsuyoshi Idé, Rudy Raymond

We discuss future directions of Blockchain as a collaborative value co-creation platform, in which network participants can gain extra insights that cannot be accessed when disconnected from the others.

Multi-Task Learning Privacy Preserving

Testing Scalable Bell Inequalities for Quantum Graph States on IBM Quantum Devices

1 code implementation25 Jan 2021 Bo Yang, Rudy Raymond, Hiroshi Imai, Hyungseok Chang, Hidefumi Hiraishi

We are able to show violations of the inequalities on various graph states by constructing low-depth quantum circuits producing them, and by applying the readout error mitigation technique.

Quantum Physics

Verifying Results of the IBM Qiskit Quantum Circuit Compilation Flow

2 code implementations4 Sep 2020 Lukas Burgholzer, Rudy Raymond, Robert Wille

In this paper, we propose an efficient scheme for quantum circuit equivalence checking---specialized for verifying results of the IBM Qiskit quantum circuit compilation flow.

Quantum Circuit Equivalence Checking Quantum Physics

Profile-guided memory optimization for deep neural networks

no code implementations26 Apr 2018 Taro Sekiyama, Takashi Imamichi, Haruki Imai, Rudy Raymond

We address this challenge by developing a novel profile-guided memory optimization to efficiently and quickly allocate memory blocks during the propagation in DNNs.

Dynamic Boltzmann Machines for Second Order Moments and Generalized Gaussian Distributions

no code implementations17 Dec 2017 Rudy Raymond, Takayuki Osogami, Sakyasingha Dasgupta

Gaussian DyBM is a DyBM that assumes the predicted data is generated by a Gaussian distribution whose first-order moment (mean) dynamically changes over time but its second-order moment (variance) is fixed.

Time Series Time Series Analysis

A Deep-Learning Approach for Operation of an Automated Realtime Flare Forecast

no code implementations6 Jun 2016 Yuko Hada-Muranushi, Takayuki Muranushi, Ayumi Asai, Daisuke Okanohara, Rudy Raymond, Gentaro Watanabe, Shigeru Nemoto, Kazunari Shibata

Automated forecasts serve important role in space weather science, by providing statistical insights to flare-trigger mechanisms, and by enabling tailor-made forecasts and high-frequency forecasts.

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