5 citations · 7 across the 5 of their papers we have counts for
4 papers · 1 filter
CrystalFramer: Rethinking the Role of Frames for SE(3)-Invariant Crystal Structure Modeling
Yusei Ito, Tatsunori Taniai, Ryo Igarashi +2
Crystal structure modeling with graph neural networks is essential for various applications in materials informatics, and capturing SE(3)-invariant geometric features is a fundamen…
Bridging Text and Crystal Structures: Literature-driven Contrastive Learning for Materials Science
Yuta Suzuki, Tatsunori Taniai, Ryo Igarashi +4
Understanding structure-property relationships is an essential yet challenging aspect of materials discovery and development. To facilitate this process, recent studies in material…
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…
A Transformer Model for Symbolic Regression towards Scientific Discovery
Florian Lalande, Yoshitomo Matsubara, Naoya Chiba +3
Symbolic Regression (SR) searches for mathematical expressions which best describe numerical datasets. This allows to circumvent interpretation issues inherent to artificial neural…