10 citations · 19 across the 7 of their papers we have counts for
7 papers
Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding
Tatsunori Taniai, Ryo Igarashi, Yuta Suzuki +4
Predicting physical properties of materials from their crystal structures is a fundamental problem in materials science. In peripheral areas such as the prediction of molecular pro…
TNF: Tri-branch Neural Fusion for Multimodal Medical Data Classification
Tong Zheng, Shusaku Sone, Yoshitaka Ushiku +2
This paper presents a Tri-branch Neural Fusion (TNF) approach designed for classifying multimodal medical images and tabular data. It also introduces two solutions to address the c…
WeaveNet for Approximating Two-sided Matching Problems
Shusaku Sone, Jiaxin Ma, Atsushi Hashimoto +2
Matching, a task to optimally assign limited resources under constraints, is a fundamental technology for society. The task potentially has various objectives, conditions, and cons…
A Critical Look at the Current Usage of Foundation Model for Dense Recognition Task
Shiqi Yang, Atsushi Hashimoto, Yoshitaka Ushiku
In recent years large model trained on huge amount of cross-modality data, which is usually be termed as foundation model, achieves conspicuous accomplishment in many fields, such…
Noisy Universal Domain Adaptation via Divergence Optimization for Visual Recognition
Qing Yu, Atsushi Hashimoto, Yoshitaka Ushiku
To transfer the knowledge learned from a labeled source domain to an unlabeled target domain, many studies have worked on universal domain adaptation (UniDA), where there is no con…
DeMIAN: Deep Modality Invariant Adversarial Network
Kuniaki Saito, Yusuke Mukuta, Yoshitaka Ushiku +1
Obtaining common representations from different modalities is important in that they are interchangeable with each other in a classification problem. For example, we can train a cl…