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| http://dx.doi.org/10.3389/fnins.2018.00578 | DOI Listing |
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Restricted Boltzmann Machines Implemented by Spin-Orbit Torque Magnetic Tunnel Junctions.
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Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100190, China.
Artificial intelligence has surged forward with the advent of generative models, which rely heavily on stochastic computing architectures enhanced by true random number generators with adjustable sampling probabilities. In this study, we develop spin-orbit torque magnetic tunnel junctions (SOT-MTJs), investigating their sigmoid-style switching probability as a function of the driving voltage. This feature proves to be ideally suited for stochastic computing algorithms such as the restricted Boltzmann machines (RBM) prevalent in pretraining processes.
View Article and Find Full Text PDFAuditory noise improves balance control by cross-modal stochastic resonance.
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Vocational College of Osaka Judo Therapist Association, 3-10-3 Utsubohommachi, Nishi-ku, Osaka 550-0004, Japan.
It is known that enhanced somatosensory function leads to improved balance, and somatosensory function can be enhanced by the appropriate level of mechanical, visual, or auditory noise. In this study, we tested the potential benefit of an auditory noise on balance control. We first assessed static balance by measuring 10 times the duration of standing on the toes of one leg with closed eyes.
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View Article and Find Full Text PDFGalvanic Vestibular Stimulation Produces Cross-Modal Improvements in Visual Thresholds.
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Ann & H.J. Smead Department of Aerospace Engineering Sciences, University of Colorado-Boulder, Boulder, CO, United States.
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View Article and Find Full Text PDFSemantics-Aware Spatial-Temporal Binaries for Cross-Modal Video Retrieval.
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With the current exponential growth of video-based social networks, video retrieval using natural language is receiving ever-increasing attention. Most existing approaches tackle this task by extracting individual frame-level spatial features to represent the whole video, while ignoring visual pattern consistencies and intrinsic temporal relationships across different frames. Furthermore, the semantic correspondence between natural language queries and person-centric actions in videos has not been fully explored.
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