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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CQ, CBE (Joint) |
2025-01-30 09:40 |
Fukuoka | (Fukuoka, Online) (Primary: On-site, Secondary: Online) |
An Empirical Study on the Applicability of GNN to Graph Reduction Tomoya Matoba, Ryotaro Matsuo, Ryo Nakamura (Fukuoka Univ.)  CQ2024-67 |
(To be available after the conference date) [more] | CQ2024-67 pp.1-6 |
| NC, NLP (Joint) |
2025-01-28 10:25 |
Osaka | (Osaka) | Periodic orbits and stability in sparse binary neural networks Ryota Toyama, Hiroki Nonaka, Toshimichi saito (HU) NLP2024-93 |
(To be available after the conference date) [more] | NLP2024-93 pp.7-10 |
| NC, NLP (Joint) |
2025-01-28 11:30 |
Osaka | (Osaka) | Clustering for S-P chart based on hysteresis neural networks Seigo Nakamura, Shinya Kujirai, Kazuma Kiyohara, Toshimichi Saito (HU) NC2024-41 |
(To be available after the conference date) [more] | NC2024-41 pp.1-6 |
| NC, NLP (Joint) |
2025-01-29 13:40 |
Osaka | (Osaka) | Learning and generation of long-period rhythms using reservoir computing with slow features Yuji Kawai (Osaka Univ.), Shinya Fujii (Keio Univ.), Minoru Asada (IPUT/Osaka Univ./NICT/Chubu Univ.) NC2024-54 |
(To be available after the conference date) [more] | NC2024-54 pp.72-73 |
| NC, NLP (Joint) |
2025-01-29 14:30 |
Osaka | (Osaka) | Effects of Introducing Gap Junctions into Spiking Neural Networks on Handwritten Digit Classification Shinnosuke Touda, Akito Morita, Hirotsugu Okuno (OIT) NC2024-56 |
(To be available after the conference date) [more] | NC2024-56 pp.79-83 |
| VLD, RECONF | 2025-01-17 10:30 |
Kanagawa | Yokohama Technology Campus Flagship Building (Kanagawa, Online) (Primary: On-site, Secondary: Online) |
Investigation of patch-based neural networks for super-resolution hardware Junya Kibushi, Cong-Kha Pham (UEC) VLD2024-91 RECONF2024-121 |
Single image super-resolution is a technique for estimating a high-resolution image from a single low-resolution image. ... [more] | VLD2024-91 RECONF2024-121 pp.87-90 |
| MSS, SS | 2025-01-12 16:40 |
Kagoshima | (Kagoshima) | [Invited Talk]
Exploring the Role of System and Control in the IoT/AI Era Ryosuke Adachi (Yamaguchi Univ.) MSS2024-54 SS2024-33 |
With the rapid spread of IoT, social systems such as electric power systems, transportation systems, and urban systems b... [more] | MSS2024-54 SS2024-33 p.65 |
| IBISML | 2024-12-20 10:30 |
Hokkaido | Lecture room 1 (D101), Graduate School of Environmental Science (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Training Deep Neural Networks for Fast Data Assimilation Yuta Ono (UTokyo), Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda (PFN) IBISML2024-36 |
Data assimilation (DA) is imperative to achieve accurate state estimation from observations and numerical simulations. A... [more] | IBISML2024-36 pp.34-40 |
| EMT, IEE-EMT | 2024-11-26 15:55 |
Shizuoka | Shizuoka Convestion & Arts Center (Shizuoka) | On applying transfer learning into the neural network method for electromagnetic analysis Kazuhiro Fujita (Saitama IT) EMT2024-61 |
The author has been working on the development of the neural network methods for electromagnetic analysis. In this repor... [more] | EMT2024-61 pp.13-16 |
| EMT, IEE-EMT | 2024-11-28 10:25 |
Shizuoka | Shizuoka Convestion & Arts Center (Shizuoka) | Proposal of Extended Liquid Time-Constant Neural Networks to Solve Partial Differential Equations Justin Jun Wilkins, Yukihisa Suzuki (Tokyo Metropolitan Univ.) EMT2024-77 |
The purpose of this study is to develop a machine learning model using deep learning as a surrogate model for analysing ... [more] | EMT2024-77 pp.96-101 |
| PN | 2024-11-18 13:55 |
Oita | (Oita, Online) (Primary: On-site, Secondary: Online) |
Sequence Estimation Method to Alleviate Spectrum Narrowing Reiji Higuchi, Taisei Sekizuka, Kazato Satake, Takuma Kuno (Nagoya Univ.), Yojiro Mori (Toyota Tech. Inst.), Hiroshi Hasegawa (Nagoya Univ.) PN2024-29 |
To efficiently increase network capacity, it is crucial to accelerate signal rates per wavelength and densify wavelength... [more] | PN2024-29 pp.12-16 |
| SITE, LOIS, ISEC | 2024-11-15 13:05 |
Fukuoka | (Fukuoka) | A Study on Plaintext Prediction for a Lightweight Block Cipher Midori Using Neural Network Eiki Furutsu, Shunsuke Araki (Kyutech) ISEC2024-81 SITE2024-78 LOIS2024-45 |
Midori is a lightweight block cipher designed for low power consumption. Since many analysis papers have been published... [more] |
ISEC2024-81 SITE2024-78 LOIS2024-45 pp.126-133 |
| CCS | 2024-11-13 10:00 |
Miyagi | Tohoku University (Miyagi) | Clustering for S-P charts based on Recurrent Neural Networks Kazuma Kiyohara, Toshimichi Saito (HU) CCS2024-50 |
This paper studies a clustering method for binary data sets based on discrete-time recurrent neural networks(DT-RNNs). T... [more] | CCS2024-50 pp.41-46 |
| CCS | 2024-11-13 10:25 |
Miyagi | Tohoku University (Miyagi) | Analysis of co-existing equilibrium points in hysteresis neural networks Shinya Kujirai, Toshimichi Saito (HU) CCS2024-51 |
This paper studies stability of co-existing multiple equilibrium points in hysteresis neural networks. The neural networ... [more] | CCS2024-51 pp.47-50 |
| CCS | 2024-11-13 10:50 |
Miyagi | Tohoku University (Miyagi) | Analysis of periodic orbits on Sparse Binary Neural Networks Hiroki Nonaka, Toshimichi Saito (HU) CCS2024-52 |
This paper studies sparse binary neural networks characterized by local binary connection parameters and signum activati... [more] | CCS2024-52 pp.51-54 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] | 2024-11-12 14:30 |
Oita | COMPAL HALL (Oita, Online) (Primary: On-site, Secondary: Online) |
Efficient inference method using adaptive variable time steps in SNN Naoya Watanabe, Yoshinori Takeuchi (Kindai) VLD2024-29 ICD2024-47 DC2024-51 RECONF2024-59 |
Artificial intelligence is now widely used in private life and business, and its application requires learning that invo... [more] | VLD2024-29 ICD2024-47 DC2024-51 RECONF2024-59 pp.14-19 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] | 2024-11-13 10:30 |
Oita | COMPAL HALL (Oita, Online) (Primary: On-site, Secondary: Online) |
Prametric Yield Estimation using Bayesian Neural Networks Yuto Moriguchi, Nobukazu Takai (KIT) VLD2024-51 ICD2024-69 DC2024-73 RECONF2024-81 |
The automation of analog circuit design using machine learning techniques such as reinforcement learning and black-box o... [more] | VLD2024-51 ICD2024-69 DC2024-73 RECONF2024-81 pp.137-141 |
| SDM | 2024-11-08 11:20 |
Tokyo | (Tokyo, Online) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Automation of Cryogenic Device Modeling Utilizing Neural Networks Takumi Inaba, Yusuke Chiashi, Minoru Ogura, Hidehiro Asai, Hiroshi Fuketa, Hiroshi Oka, Shota Iizuka, Kimihiko Kato, Shunsuke Shitakata, Takahiro Mori (AIST) SDM2024-60 |
Automated device model parameter extraction for cryogenic MOSFETs was examined. Transfer learning neural network model w... [more] | SDM2024-60 pp.22-25 |
| MRIS, CPM, ITE-MMS [detail] | 2024-11-01 09:20 |
Nagano | Nagano Camp. Shinshu Univ. + Online (Nagano, Online) (Primary: On-site, Secondary: Online) |
Controlling time constant of an oxide-based leaky-integrating transistor for biomimetic information processing Yuuki Koh (TUS/AIST), Ai Kitoh, Hisashi Inoue (AIST), Masahumi Tamura (TUS), Isao H. Inoue (AIST) MRIS2024-20 CPM2024-49 |
Reservoir computing is a model that mimics biological neural networks and excels at processing time series data. The per... [more] | MRIS2024-20 CPM2024-49 pp.49-52 |
| MRIS, CPM, ITE-MMS [detail] | 2024-11-01 12:10 |
Nagano | Nagano Camp. Shinshu Univ. + Online (Nagano, Online) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Development of oxide-based leaky-integrating transistor for spiking neural networks Hisashi Inoue (AIST), Hiroto Tamura (Univ. Tokyo), Ai Kitoh (AIST), Xiangyu Chen, Zolboo Byambadorj (Univ. Tokyo), Takeaki Yajima (Kyushu Univ.), Yasushi Hotta (Univ. Hyogo), Tetsuya Iizuka (Univ. Tokyo), Gouhei Tanaka (Univ. Tokyo/Nagoya Inst. Tech.), Isao Inoue (AIST) MRIS2024-26 CPM2024-55 |
Biomimetic computing aims to realize energy-efficient information processing by mimicking the behavior of biological neu... [more] | MRIS2024-26 CPM2024-55 pp.77-80 |
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