activity
20182023
most citedRecent Advances in Physical Reservoir Computing: A Review

2.2k citations · 2.2k across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2023★ 2 cited

MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network

Akihiro Kishimoto, Hiroshi Kajino, Masataka Hirose +6

Property prediction plays an important role in material discovery. As an initial step to eventually develop a foundation model for material science, we introduce a new autoencoder…

cond-mat.mtrl-sci2022

AI powered, automated discovery of polymer membranes for carbon capture

Ronaldo Giro, Hsianghan Hsu, Akihiro Kishimoto +6

The generation of molecules with Artificial Intelligence (AI) is poised to revolutionize materials discovery. Potential applications range from development of potent drugs to effic…

cs.LG2022★ 37 cited

Accelerating Material Design with the Generative Toolkit for Scientific Discovery

Matteo Manica, Jannis Born, Joris Cadow +21

With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery. They harness powerful represe…

cs.CE2021★ 3 cited

Molecule Generation Experience: An Open Platform of Material Design for Public Users

Seiji Takeda, Toshiyuki Hama, Hsiang-Han Hsu +10

Artificial Intelligence (AI)-driven material design has been attracting great attentions as a groundbreaking technology across a wide spectrum of industries. Molecular design is pa…

cs.CE2020★ 4 cited

Molecular Inverse-Design Platform for Material Industries

Seiji Takeda, Toshiyuki Hama, Hsiang-Han Hsu +17

The discovery of new materials has been the essential force which brings a discontinuous improvement to industrial products' performance. However, the extra-vast combinatorial desi…

cs.CE2020★ 7 cited

AI-driven Inverse Design System for Organic Molecules

Seiji Takeda, Toshiyuki Hama, Hsiang-Han Hsu +7

Designing novel materials that possess desired properties is a central need across many manufacturing industries. Driven by that industrial need, a variety of algorithms and tools…

cs.ET2018★ 2.2k cited

Recent Advances in Physical Reservoir Computing: A Review

Gouhei Tanaka, Toshiyuki Yamane, Jean Benoit Héroux +6

Reservoir computing is a computational framework suited for temporal/sequential data processing. It is derived from several recurrent neural network models, including echo state ne…