no code implementations • 22 Dec 2023 • Hisaichi Shibata
Utilizing this scale, I tested language models for their ability to acquire character-level equivariance.
no code implementations • 21 Feb 2023 • Hisaichi Shibata, Soichiro Miki, Yuta Nakamura
The purpose of this study is to develop an AI agent that can play Werewolf through natural language conversations.
no code implementations • 20 Dec 2022 • Hisaichi Shibata, Shouhei Hanaoka, Yang Cao, Masatoshi Yoshikawa, Tomomi Takenaga, Yukihiro Nomura, Naoto Hayashi, Osamu Abe
To release and use medical images, we need an algorithm that can simultaneously protect privacy and preserve pathologies in medical images.
no code implementations • 23 Aug 2022 • Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Naoto Hayashi, Osamu Abe
From birth to death, we all experience surprisingly ubiquitous changes over time due to aging.
no code implementations • 9 Apr 2021 • Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Tomomi Takenaga, Naoto Hayashi, Osamu Abe
Here, we propose X2CT-FLOW for the maximum a posteriori (MAP) reconstruction of a three-dimensional (3D) chest CT image from a single or a few two-dimensional (2D) projection images using a progressive flow-based deep generative model, especially for ultra low-dose protocols.
no code implementations • 18 Feb 2020 • Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Naoto Hayashi, Osamu Abe
In general, adversarial perturbations superimposed on inputs are realistic threats for a deep neural network (DNN).