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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 58  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IBISML, IPSJ-CVIM 2024-03-03
15:15
Hiroshima Hiroshima Univ. Higashi-Hiroshima campus
(Primary: On-site, Secondary: Online)
Attention Guidance Based on Predicate Logic for Text-to-Image Diffusion Models
Kota Sueyoshi, Takashi Matsubara (Osaka Univ.) IBISML2023-41
 [more] IBISML2023-41
pp.6-13
CCS 2023-03-27
09:00
Hokkaido RUSUTSU RESORT Medical Image Segmentation with Inverse Heat Dissipation Model
Yu Kashihara, Takashi Matsubara (Osaka Univ.) CCS2022-82
The diffusion model is a generative model based on stochastic transitions and has been successfully used to generate
an... [more]
CCS2022-82
pp.107-112
CCS 2023-03-27
09:20
Hokkaido RUSUTSU RESORT Learning Commutative Vector Field in Latent Space of Deep Generative Model
Takehiro Aoshima, Takashi Matsubara (Osaka Univ.) CCS2022-83
Deep generative models, such as generative adversarial networks (GANs), are known for generating high-quality images. Ho... [more] CCS2022-83
pp.113-116
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2022-06-27
15:55
Okinawa
(Primary: On-site, Secondary: Online)
NC2022-5 IBISML2022-5 (To be available after the conference date) [more] NC2022-5 IBISML2022-5
pp.47-52
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2022-06-28
10:05
Okinawa
(Primary: On-site, Secondary: Online)
Learning Attribute Vector Fields in GAN Latent Space
Takehiro Aoshima, Takashi Matsubara (Osaka Univ.) NC2022-12 IBISML2022-12
Generative Adversarial Networks (GANs) can generate a great variety of high-quality images.
Despite their ability to g... [more]
NC2022-12 IBISML2022-12
pp.94-99
CCS 2022-03-27
15:15
Hokkaido RUSUTSU RESORT HOTEL & CONVENTION
(Primary: On-site, Secondary: Online)
Learning Physical Systems with Imbalance-Aware Deep Learning
Takahito Yoshida (Osaka Univ.), Takaharu Yaguchi (Kobe Univ.), Takashi Matsubara (Osaka Univ.) CCS2021-47
 [more] CCS2021-47
pp.66-71
CCS 2022-03-27
15:40
Hokkaido RUSUTSU RESORT HOTEL & CONVENTION
(Primary: On-site, Secondary: Online)
Evaluation of Industrial Anomaly Detection using Diffusion Model
Yu Kashihara, Takashi Matsubara (Osaka Univ.) CCS2021-48
Anomaly detection by generative models is achieved by comparing the reconstruction and the original image. However, exis... [more] CCS2021-48
pp.72-77
CCS 2022-03-27
16:05
Hokkaido RUSUTSU RESORT HOTEL & CONVENTION
(Primary: On-site, Secondary: Online)
Range-Equivariant Convolution for Spherical Projection-based Segmentation of LiDAR Point Clouds
Hidetaka Marumo, Takashi Matsubara (Osaka Univ) CCS2021-49
In autonomous driving, LiDAR point clouds segmentation has attracted much attention. For efficiency and ease of design, ... [more] CCS2021-49
pp.78-83
IBISML 2022-03-08
13:05
Online Online [Invited Talk] ---
Takashi Matsubara (Osaka Univ.) IBISML2021-34
Deep learning is being considered as the most promising approach to building an artificial intelligence (AI) system; it ... [more] IBISML2021-34
p.27
RECONF, VLD, CPSY, IPSJ-ARC, IPSJ-SLDM [detail] 2022-01-25
09:30
Online Online GPU acceleration of algorithm for minimal distance approximate calculation between two objects
Masumi Fukuta, Takakazu Kurokawa, Takashi Matsubara, Keisuke Iwai (NDA) VLD2021-62 CPSY2021-31 RECONF2021-70
(To be available after the conference date) [more] VLD2021-62 CPSY2021-31 RECONF2021-70
pp.73-77
CCS 2021-11-18
16:25
Osaka Osaka Univ.
(Primary: On-site, Secondary: Online)
Memory Efficient Training of Neural ODE by Symplectic Adjoint Method
Takashi Matsubara, Yuto Miyatake (Osaka Univ.), Takaharu Yaguchi (Kobe Univ.) CCS2021-23
Neural ODE learns an ordinary differential equation using neural networks, thereby modeling a continuous-time dynamics a... [more] CCS2021-23
pp.31-36
CCS 2021-11-19
11:10
Osaka Osaka Univ.
(Primary: On-site, Secondary: Online)
Toward Human Cognition-inspired High-Level Decision Making For Hierarchical Reinforcement Learning Agents
Rousslan Fernand Julien Dossa (Kobe Univ.), Takashi Matsubara (Osaka Univ.) CCS2021-28
Hierarchical reinforcement learning (HRL) methods aim to leverage the concept of temporal abstraction to efficiently sol... [more] CCS2021-28
pp.61-66
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2021-06-28
13:25
Online Online Training Neural ODE by Symplectic Integrator
Takashi Matsubara, Yuto Miyatake (Osaka Univ.), Takaharu Yaguchi (Kobe Univ.) NC2021-2 IBISML2021-2
A differential equation model using neural networks, neural ODE, enables use to model a continuous-time dynamics and pr... [more] NC2021-2 IBISML2021-2
pp.9-14
MI 2021-03-15
15:15
Online Online Deep State-Space Modeling of FMRI Images with Disentangle Attributes
Koki Kusano (Kobe Univ.), Takashi Matsubara (Osaka Univ.), Kuniaki Uehara (Osaka Gakuin Univ.) MI2020-59
As well as the disorder and other targets, nuisance attributes such as age, gender, and scanner specifications underlie ... [more] MI2020-59
pp.56-61
MI 2021-03-17
13:45
Online Online Medical Image Style Translation by Adversarial Training with Paired Inputs
Kazuki Fujioka (Kobe Univ.), Takashi Matsubara (Osaka Univ.), Kuniaki Uehara (Osaka Gakuin Univ.) MI2020-96
Medical image diagnosis by artificial intelligence requires a large amount of data for learning. However, preparing such... [more] MI2020-96
pp.212-217
EA, ASJ-H, EMM 2020-11-20
09:00
Online Online [Poster Presentation] Improving wavelet-synchrosqueezing transform with calculating angular frequency using time shift
Akira Kakutani, Takashi Matsubara, Keisuke Iwai, Takakazu Kurokawa (NDA) EA2020-21 EMM2020-36
Time-frequency analysis is mainly used for analyzing acoustic signals. Short-time Fourier transform by Allen, et al. and... [more] EA2020-21 EMM2020-36
pp.1-5
IBISML 2020-10-20
10:25
Online Online Few-shot Anomaly Detection by Extracting Common Feature of Set Data
Kazuki Sato (Kobe Univ.), Satoshi Nakata (The KAITEKI Institute), Takashi Matsubara (Osaka Univ.), Kuniaki Uehara (Osaka Gakuin Univ.) IBISML2020-9
 [more] IBISML2020-9
pp.8-13
IN, CCS
(Joint)
2020-08-03
15:35
Online Online [Invited Talk] Current Status and Future Prospects for Image-Based Anomaly Detection
Kazuki Sato (Kobe Univ.), Takashi Matsubara (Osaka Univ.), Kuniaki Uehara (Osaka Gakuin Univ.) CCS2020-12
 [more] CCS2020-12
pp.1-4
IBISML 2020-03-11
09:45
Kyoto Kyoto University
(Cancelled but technical report was issued)
Knowledge Graph Completion by Separating Transition and Score Functions
Kenta Hama, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) IBISML2019-41
A knowledge graph is represented by a set of two entities and the relations, and used for various tasks such as informat... [more] IBISML2019-41
pp.59-62
IBISML 2020-03-11
15:10
Kyoto Kyoto University
(Cancelled but technical report was issued)
Fairness Causes Vulnerability to Adversarial Attacks
Koki Wataoka, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) IBISML2019-48
When using machine learning models in society, it is essential to be ensure classifiers are fair to race and gender. In ... [more] IBISML2019-48
pp.101-105
 Results 1 - 20 of 58  /  [Next]  
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