94 citations · 323 across the 29 of their papers we have counts for
4 papers · 1 filter
A Novel Predictive-Coding-Inspired Variational RNN Model for Online Prediction and Recognition
Ahmadreza Ahmadi, Jun Tani
This study introduces PV-RNN, a novel variational RNN inspired by the predictive-coding ideas. The model learns to extract the probabilistic structures hidden in fluctuating tempor…
A Dynamic Neural Network Approach to Generating Robot's Novel Actions: A Simulation Experiment
Jungsik Hwang, Jun Tani
In this study, we investigate how a robot can generate novel and creative actions from its own experience of learning basic actions. Inspired by a machine learning approach to comp…
Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization
German I. Parisi, Jun Tani, Cornelius Weber +1
Artificial autonomous agents and robots interacting in complex environments are required to continually acquire and fine-tune knowledge over sustained periods of time. The ability…
Generating Goal-Directed Visuomotor Plans Based on Learning Using a Predictive Coding-type Deep Visuomotor Recurrent Neural Network Model
Minkyu Choi, Takazumi Matsumoto, Minju Jung +1
The current paper presents how a predictive coding type deep recurrent neural networks can generate vision-based goal-directed plans based on prior learning experience by examining…