フォロー
Ikuro Sato
Ikuro Sato
Tokyo Institute of Technology, Denso IT Laboratory
確認したメール アドレス: core.d-itlab.co.jp
タイトル
引用先
引用先
Group-theoretical construction of extended baryon operators in lattice QCD
S Basak, RG Edwards, GT Fleming, UM Heller, C Morningstar, D Richards, ...
Physical Review D—Particles, Fields, Gravitation, and Cosmology 72 (9), 094506, 2005
1932005
Apac: Augmented pattern classification with neural networks
I Sato, H Nishimura, K Yokoi
arXiv preprint arXiv:1505.03229, 2015
1762015
Lattice QCD determination of patterns of excited baryon states
S Basak, RG Edwards, GT Fleming, KJ Juge, A Lichtl, C Morningstar, ...
Physical Review D—Particles, Fields, Gravitation, and Cosmology 76 (7), 074504, 2007
1242007
Finite volume corrections to scattering
PF Bedaque, I Sato, A Walker-Loud
Physical Review D—Particles, Fields, Gravitation, and Cosmology 73 (7), 074501, 2006
752006
Moving object recognition systems, moving object recognition programs, and moving object recognition methods
I Sato, Y Tamatsu, K Goto
US Patent 9,824,586, 2017
682017
Method and system for obtaining improved structure of a target neural network
Y Tamatsu, I Sato
US Patent App. 14/317,261, 2015
642015
Implicit neural representations for variable length human motion generation
P Cervantes, Y Sekikawa, I Sato, K Shinoda
European Conference on Computer Vision, 356-372, 2022
522022
Fitting two nucleons inside a box: Exponentially suppressed corrections to Lüscher’s formula
I Sato, PF Bedaque
Physical Review D—Particles, Fields, Gravitation, and Cosmology 76 (3), 034502, 2007
482007
Clebsch-Gordan construction of lattice interpolated fields for excited baryons
S Basak, R Edwards, GT Fleming, UM Heller, C Morningstar, D Richards, ...
Physical Review D—Particles, Fields, Gravitation, and Cosmology 72 (7), 074501, 2005
412005
Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers
Y Oyama, A Nomura, I Sato, H Nishimura, Y Tamatsu, S Matsuoka
2016 IEEE International Conference on Big Data (Big Data), 66-75, 2016
322016
Generating easy-to-understand referring expressions for target identifications
M Tanaka, T Itamochi, K Narioka, I Sato, Y Ushiku, T Harada
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
192019
Crossing obstacle detection with a vehicle-mounted camera
I Sato, C Yamano, H Yanagawa
2011 IEEE Intelligent Vehicles Symposium (IV), 60-65, 2011
192011
Combining quark and link smearing to improve extended baryon operators
A Lichtl, S Basak, R Edwards, GT Fleming, UM Heller, C Morningstar, ...
arXiv preprint hep-lat/0509179, 2005
162005
Detection device, detection program, detection method, vehicle equipped with detection device, parameter calculation device, parameter calculating parameters, parameter …
Y Tamatsu, K Yokoi, I Sato
US Patent App. 14/722,397, 2015
142015
Feature space particle inference for neural network ensembles
S Yashima, T Suzuki, K Ishikawa, I Sato, R Kawakami
International Conference on Machine Learning, 25452-25468, 2022
132022
Adversarial transformations for semi-supervised learning
T Suzuki, I Sato
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5916-5923, 2020
132020
Analysis of N⋆ spectra using matrices of correlation functions based on irreducible baryon operators
S Basak, R Edwards, R Fiebig, GT Fleming, UM Heller, C Morningstar, ...
Nuclear Physics B-Proceedings Supplements 140, 278-280, 2005
132005
Combining quark and link smearing to improve extended baryon operators, PoS LAT2005 (2006) 076
S Basak, I Sato, S Wallace, R Edwards, D Richards, GT Fleming
arXiv preprint hep-lat/0509179 3 (1), 0
13
Method and apparatus for detecting moving objects
K Goto, I Sato
US Patent 9,852,334, 2017
122017
Discriminator, discrimination program, and discrimination method
Y Tamatsu, I Sato
US Patent App. 14/540,295, 2015
122015
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論文 1–20