6 citations · 6 across the 3 of their papers we have counts for
8 papers
Probing conformational dynamics of antibodies with geometric simulations
Andrejs Tucs, Koji Tsuda, Adnan Sljoka
This chapter describes the application of constrained geometric simulations for prediction of antibody structural dynamics. We utilize constrained geometric simulations method FROD…
Continuous black-box optimization with quantum annealing and random subspace coding
Syun Izawa, Koki Kitai, Shu Tanaka +2
A black-box optimization algorithm such as Bayesian optimization finds extremum of an unknown function by alternating inference of the underlying function and optimization of an ac…
Optimization of heterogeneous ternary Li3PO4-Li3BO3-Li2SO4 mixture for Li-ion conductivity by machine learning
Kenji Homma, Yu Liu, Masato Sumita +5
Mixing heterogeneous Li-ion conductive materials is one of potential ways to enhance the Li-ion conductivity more than that of the parent materials. However, the development of the…
Leveraging Legacy Data to Accelerate Materials Design via Preference Learning
Xiaolin Sun, Zhufeng Hou, Masato Sumita +3
Machine learning applications in materials science are often hampered by shortage of experimental data. Integration with legacy data from past experiments is a viable way to solve…
Deep learning-based quality filtering of mechanically exfoliated 2D crystals
Yu Saito, Kento Shin, Kei Terayama1 +7
Two-dimensional (2D) crystals are attracting growing interest in various research fields such as engineering, physics, chemistry, pharmacy and biology owing to their low dimensiona…
Expanding the horizon of automated metamaterials discovery via quantum annealing
Koki Kitai, Jiang Guo, Shenghong Ju +4
Complexity of materials designed by machine learning is currently limited by the inefficiency of classical computers. We show how quantum annealing can be incorporated into automat…