38 citations · 73 across the 11 of their papers we have counts for
5 papers · 1 filter
ContinuouSP: Generative Model for Crystal Structure Prediction with Invariance and Continuity
Yuji Tone, Masatoshi Hanai, Mitsuaki Kawamura +2
The discovery of new materials using crystal structure prediction (CSP) based on generative machine learning models has become a significant research topic in recent years. In this…
Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation
Xiaohang Xu, Toyotaro Suzumura, Jiawei Yong +5
Next Point-of-Interest (POI) recommendation plays a crucial role in urban mobility applications. Recently, POI recommendation models based on Graph Neural Networks (GNN) have been…
On Data Imbalance in Molecular Property Prediction with Pre-training
Limin Wang, Masatoshi Hanai, Toyotaro Suzumura +2
Revealing and analyzing the various properties of materials is an essential and critical issue in the development of materials, including batteries, semiconductors, catalysts, and…
Is Self-Supervised Pretraining Good for Extrapolation in Molecular Property Prediction?
Shun Takashige, Masatoshi Hanai, Toyotaro Suzumura +2
The prediction of material properties plays a crucial role in the development and discovery of materials in diverse applications, such as batteries, semiconductors, catalysts, and…
mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations
Toyotaro Suzumura, Akiyoshi Sugiki, Hiroyuki Takizawa +30
The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability…