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07/22/2023
On-Robot Bayesian Reinforcement Learning for POMDPs
Robot learning is often difficult due to the expense of gathering data. ...
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06/24/2023
Learning from Pixels with Expert Observations
In reinforcement learning (RL), sparse rewards can present a significant...
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11/03/2022
Leveraging Fully Observable Policies for Learning under Partial Observability
Reinforcement learning in partially observable domains is challenging du...
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09/03/2022
vieCap4H-VLSP 2021: Vietnamese Image Captioning for Healthcare Domain using Swin Transformer and Attention-based LSTM
This study presents our approach on the automatic Vietnamese image capti...
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04/02/2022
Hierarchical Reinforcement Learning under Mixed Observability
The framework of mixed observable Markov decision processes (MOMDP) mode...
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02/17/2022
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs
While reinforcement learning (RL) has made great advances in scalability...
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10/25/2021
Recurrent Off-policy Baselines for Memory-based Continuous Control
When the environment is partially observable (PO), a deep reinforcement ...
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09/06/2021
Fruit-CoV: An Efficient Vision-based Framework for Speedy Detection and Diagnosis of SARS-CoV-2 Infections Through Recorded Cough Sounds
SARS-CoV-2 is colloquially known as COVID-19 that had an initial outbrea...
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03/22/2021
Multi-directional Bicycle Robot for Steel Structure Inspection
This paper presents a novel design of a multi-directional bicycle robot,...
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10/19/2020
Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability
Many important robotics problems are partially observable in the sense t...
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09/08/2020
A Deep Learning-Based Autonomous RobotManipulator for Sorting Application
Robot manipulation and grasping mechanisms have received considerable at...
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02/27/2020
Review, Analyze, and Design a Comprehensive Deep Reinforcement Learning Framework
Reinforcement learning (RL) has emerged as a standard approach for build...
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02/19/2019
Deep Reinforcement Learning using Genetic Algorithm for Parameter Optimization
Reinforcement learning (RL) enables agents to take decision based on a r...
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09/16/2018
Deep Learning with Experience Ranking Convolutional Neural Network for Robot Manipulator
Supervised learning, more specifically Convolutional Neural Networks (CN...
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11/28/2017
Semi-supervised learning of hierarchical representations of molecules using neural message passing
With the rapid increase of compound databases available in medicinal and...
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11/01/2017
Spatial Statistical Downscaling for Constructing High-Resolution Nature Runs in Global Observing System Simulation Experiments
Observing system simulation experiments (OSSEs) have been widely used as...
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12/31/2012