Virtual Reality as a User-friendly Interface for Learning from Demonstration
We use Virtual Reality as an intuitive interface for Imitation Learning to supervise a deep neural network based visual attention model.
We use Virtual Reality as an intuitive interface for Imitation Learning to supervise a deep neural network based visual attention model.
A generative model for faces based on Conditional VAE-GAN. – M. Suzuki
Joint work with The University of Tokyo Hospital. CNN, VAE, Generative Models, etc. – K. Nakayama, et al.
High-performance Stacked denoising Autoencoder enhanced by CrossPre (Cross-Layer Pretraining). – K.Nakayama
We are organising a special interest group on deep learning and several lecture series of deep learning – Deeplearning.jp | AIL.tokyo
To enhance computational performance on deep learning algorithms, we are working on projects such as GPU system virtualization and distributed GPU computation models. We are also providing iLect, a GPU-enabled programming environment accessible by Web broseewsers. – iLect | HPC
Evolutional deep learning algorithms towards flexible networks. – H. Kurotaki
Sensors, CNN, Model Compression for limited resource environment. – Y. Iwasawa
TBA. – N. Nonaka, et al.