Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Okuno, Tomoyuki"'
Autor:
Yang, Huanrui, Huang, Yafeng, Dong, Zhen, Gudovskiy, Denis A, Okuno, Tomoyuki, Nakata, Yohei, Du, Yuan, Keutzer, Kurt, Zhang, Shanghang
The impact of quantization on the overall performance of deep learning models is a well-studied problem. However, understanding and mitigating its effects on a more fine-grained level is still lacking, especially for harder tasks such as object detec
Externí odkaz:
http://arxiv.org/abs/2407.03442
Normalizing flow-based generative models have been widely used in applications where the exact density estimation is of major importance. Recent research proposes numerous methods to improve their expressivity. However, conditioning on a context is l
Externí odkaz:
http://arxiv.org/abs/2406.00578
Autor:
Zhang, Rongyu, Cai, Zefan, Yang, Huanrui, Liu, Zidong, Gudovskiy, Denis, Okuno, Tomoyuki, Nakata, Yohei, Keutzer, Kurt, Chang, Baobao, Du, Yuan, Du, Li, Zhang, Shanghang
Finetuning a pretrained vision model (PVM) is a common technique for learning downstream vision tasks. However, the conventional finetuning process with randomly sampled data points results in diminished training efficiency. To address this drawback,
Externí odkaz:
http://arxiv.org/abs/2401.07853
Autor:
Zhang, Rongyu, Luo, Yulin, Liu, Jiaming, Yang, Huanrui, Dong, Zhen, Gudovskiy, Denis, Okuno, Tomoyuki, Nakata, Yohei, Keutzer, Kurt, Du, Yuan, Zhang, Shanghang
The Mixture-of-Experts (MoE) approach has demonstrated outstanding scalability in multi-task learning including low-level upstream tasks such as concurrent removal of multiple adverse weather effects. However, the conventional MoE architecture with p
Externí odkaz:
http://arxiv.org/abs/2312.16610
Autor:
Chen, Anthony, Yang, Huanrui, Gan, Yulu, Gudovskiy, Denis A, Dong, Zhen, Wang, Haofan, Okuno, Tomoyuki, Nakata, Yohei, Keutzer, Kurt, Zhang, Shanghang
Uncertainty estimation is crucial for machine learning models to detect out-of-distribution (OOD) inputs. However, the conventional discriminative deep learning classifiers produce uncalibrated closed-set predictions for OOD data. A more robust class
Externí odkaz:
http://arxiv.org/abs/2312.09148
Recent semantic segmentation models accurately classify test-time examples that are similar to a training dataset distribution. However, their discriminative closed-set approach is not robust in practical data setups with distributional shifts and ou
Externí odkaz:
http://arxiv.org/abs/2305.09610
Autor:
Yu, Jinze, Liu, Jiaming, Wei, Xiaobao, Zhou, Haoyi, Nakata, Yohei, Gudovskiy, Denis, Okuno, Tomoyuki, Li, Jianxin, Keutzer, Kurt, Zhang, Shanghang
Recently, DEtection TRansformer (DETR), an end-to-end object detection pipeline, has achieved promising performance. However, it requires large-scale labeled data and suffers from domain shift, especially when no labeled data is available in the targ
Externí odkaz:
http://arxiv.org/abs/2205.01643
Autor:
Tanaka, Takaaki, Okuno, Tomoyuki, Uchida, Hiroyuki, Yamaguchi, Hiroya, Lee, Shiu-Hang, Maeda, Keiichi, Williams, Brian J.
Publikováno v:
2021, ApJL, 906, L3
In spite of their importance as standard candles in cosmology and as major major sites of nucleosynthesis in the Universe, what kinds of progenitor systems lead to type Ia supernovae (SN) remains a subject of considerable debate in the literature. Th
Externí odkaz:
http://arxiv.org/abs/2012.13622
Autor:
Okuno, Tomoyuki, Tanaka, Takaaki, Uchida, Hiroyuki, Aharonian, Felix A., Uchiyama, Yasunobu, Tsuru, Takeshi Go, Matsuda, Masamune
Publikováno v:
2020, ApJ, 894, 50
Analyzing Chandra data of Tycho's supernova remnant (SNR) taken in 2000, 2003, 2007, 2009, and 2015, we search for time variable features of synchrotron X-rays in the southwestern part of the SNR, where stripe structures of hard X-ray emission were p
Externí odkaz:
http://arxiv.org/abs/2003.10035
Autor:
Hagino, Kouichi, Oono, Kenji, Negishi, Kousuke, Yarita, Keigo, Kohmura, Takayoshi, Tsuru, Takeshi G., Tanaka, Takaaki, Uchida, Hiroyuki, Harada, Sodai, Okuno, Tomoyuki, Kayama, Kazuho, Amano, Yuki, Matsumura, Hideaki, Mori, Koji, Takeda, Ayaki, Nishioka, Yusuke, Fukuda, Kohei, Hida, Takahiro, Yukumoto, Masataka, Arai, Yasuo, Kurachi, Ikuo, Miyoshi, Toshinobu, Kishimoto, Shunji
We report on a measurement of the size of charge clouds produced by X-ray photons in X-ray SOI (Silicon-On-Insulator) pixel sensor named XRPIX. We carry out a beam scanning experiment of XRPIX using a monochromatic X-ray beam at 5.0 keV collimated to
Externí odkaz:
http://arxiv.org/abs/1905.13381