Machine Learning / Deep Learning
Understand patterns from large-scale data.
In the field of machine learning and deep learning, technology that contributes to practical use has been born due to the recent development of computer technology and communication technology.
Now, machine learning technology is expected to solve many important issues in the real world.
The issues that we need to solve are extremely complex and diverse, including abnormality detection, automatic operation, plant and robot control, and drug discovery.
To solve these issues, PFN gathers experts from a wide range of fields around machine learning, from basic theory to actual application, and works together to conduct research.
The results obtained there will be returned in the form of paper presentations, open source library publications, and application to real systems, and will respond widely to the demands of society.
Learning-based Collision-free Planning on Arbitrary Optimization Criteria in the Latent Space through cGANs
Advanced Robotics 2023
By : Tomoki Ando, Hiroto Iino, Hiroki Mori, Ryota Torishima, Kuniyuki Takahashi, Shoichiro Yamaguchi, Daisuke Okanohara, Tetsuya Ogata
Unsupervised Learning of Equivariant Structure from Sequence
By : Takeru Miyato, Masanori Koyama, Kenji Fukumizu
Decomposing NeRF for Editing via Feature Field Distillation
By : Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann
Interactive Hyperparameter Optimization with Paintable Timelines
By : Keita Higuchi, Shotaro Sano, Takeo Igarashi
Test-time adaptation for brain tumor segmentation with cross-institutional MRI
By : Junichiro Iwasawa
Change Detection and its Variable Selection in Multivariate Time Series Using aHSIC with Improvements on the Algorithm
By : Motoki Sato