137 citations · 140 across the 6 of their papers we have counts for
6 papers
S2A2: Audio-Visual Imitation Learning for Manipulation Tasks Using Acoustic Spatial Information
Kaneyoshi Hiratsuka, Benjamin Yen, Ryosuke Kojima
Acoustic information provides rich cues about object location, material properties, and changes caused by contact or motion. This paper introduces a new set of acoustic-aware manip…
Learning Deep Input-Output Stable Dynamics
Yuji Okamoto, Ryosuke Kojima
Learning stable dynamics from observed time-series data is an essential problem in robotics, physical modeling, and systems biology. Many of these dynamics are represented as an in…
MatSat: a matrix-based differentiable SAT solver
Taisuke Sato, Ryosuke Kojima
We propose a new approach to SAT solving which solves SAT problems in vector spaces as a cost minimization problem of a non-negative differentiable cost function J^sat. In our appr…
Batched Sparse Matrix Multiplication for Accelerating Graph Convolutional Networks
Yusuke Nagasaka, Akira Nukada, Ryosuke Kojima +1
Graph Convolutional Networks (GCNs) are recently getting much attention in bioinformatics and chemoinformatics as a state-of-the-art machine learning approach with high accuracy. G…
A tensorized logic programming language for large-scale data
Ryosuke Kojima, Taisuke Sato
We introduce a new logic programming language T-PRISM based on tensor embeddings. Our embedding scheme is a modification of the distribution semantics in PRISM, one of the state-of…
Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization
Mizuho Nishio, Mitsuo Nishizawa, Osamu Sugiyama +4
We aimed to evaluate computer-aided diagnosis (CADx) system for lung nodule classification focusing on (i) usefulness of gradient tree boosting (XGBoost) and (ii) effectiveness of…