research
∙
06/29/2023
Numerical Data Imputation for Multimodal Data Sets: A Probabilistic Nearest-Neighbor Kernel Density Approach
Numerical data imputation algorithms replace missing values by estimates...
share
research
∙
04/11/2023
Habits and goals in synergy: a variational Bayesian framework for behavior
How to behave efficiently and flexibly is a central problem for understa...
research
∙
06/18/2021
Goal-Directed Planning by Reinforcement Learning and Active Inference
What is the difference between goal-directed and habitual behavior? We p...
research
∙
03/15/2021
Whole brain Probabilistic Generative Model toward Realizing Cognitive Architecture for Developmental Robots
Building a humanlike integrative artificial cognitive system, that is, a...
research
∙
08/17/2020
Imitation learning based on entropy-regularized forward and inverse reinforcement learning
This paper proposes Entropy-Regularized Imitation Learning (ERIL), which...
research
∙
12/23/2019
Variational Recurrent Models for Solving Partially Observable Control Tasks
In partially observable (PO) environments, deep reinforcement learning (...
research
∙
08/02/2019
MarmoNet: a pipeline for automated projection mapping of the common marmoset brain from whole-brain serial two-photon tomography
Understanding the connectivity in the brain is an important prerequisite...
research
∙
06/18/2019
Gap-Increasing Policy Evaluation for Efficient and Noise-Tolerant Reinforcement Learning
In real-world applications of reinforcement learning (RL), noise from in...
research
∙
02/04/2019
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
Previously, the exploding gradient problem has been explained to be cent...
research
∙
01/29/2019
Emergence of Hierarchy via Reinforcement Learning Using a Multiple Timescale Stochastic RNN
Although recurrent neural networks (RNNs) for reinforcement learning (RL...
research
∙
07/25/2018
Unbounded Output Networks for Classification
We proposed the expected energy-based restricted Boltzmann machine (EE-R...
research
∙
10/30/2017
Unifying Value Iteration, Advantage Learning, and Dynamic Policy Programming
Approximate dynamic programming algorithms, such as approximate value it...
research
∙
10/21/2015