Hai Nguyen | DeepAI

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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. ...

0 Hai Nguyen, et al. ∙

∙ 06/24/2023

Learning from Pixels with Expert Observations

In reinforcement learning (RL), sparse rewards can present a significant...

0 Minh-Huy Hoang, et al. ∙

∙ 11/03/2022

Leveraging Fully Observable Policies for Learning under Partial Observability

Reinforcement learning in partially observable domains is challenging du...

0 Hai Nguyen, et al. ∙

∙ 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...

7 Thanh Tin Nguyen, et al. ∙

∙ 04/02/2022

Hierarchical Reinforcement Learning under Mixed Observability

The framework of mixed observable Markov decision processes (MOMDP) mode...

0 Hai Nguyen, et al. ∙

∙ 02/17/2022

BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs

While reinforcement learning (RL) has made great advances in scalability...

0 Sammie Katt, et al. ∙

∙ 10/25/2021

Recurrent Off-policy Baselines for Memory-based Continuous Control

When the environment is partially observable (PO), a deep reinforcement ...

0 Zhihan Yang, et al. ∙

∙ 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...

0 Long H. Nguyen, et al. ∙

∙ 03/22/2021

Multi-directional Bicycle Robot for Steel Structure Inspection

This paper presents a novel design of a multi-directional bicycle robot,...

0 Son Thanh Nguyen, et al. ∙

∙ 10/19/2020

Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability

Many important robotics problems are partially observable in the sense t...

6 Hai Nguyen, et al. ∙

∙ 09/08/2020

A Deep Learning-Based Autonomous RobotManipulator for Sorting Application

Robot manipulation and grasping mechanisms have received considerable at...

0 Hoang-Dung Bui, et al. ∙

∙ 02/27/2020

Review, Analyze, and Design a Comprehensive Deep Reinforcement Learning Framework

Reinforcement learning (RL) has emerged as a standard approach for build...

24 Ngoc Duy Nguyen, et al. ∙

∙ 02/19/2019

Deep Reinforcement Learning using Genetic Algorithm for Parameter Optimization

Reinforcement learning (RL) enables agents to take decision based on a r...

0 Adarsh Sehgal, et al. ∙

∙ 09/16/2018

Deep Learning with Experience Ranking Convolutional Neural Network for Robot Manipulator

Supervised learning, more specifically Convolutional Neural Networks (CN...

0 Hai Nguyen, et al. ∙

∙ 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...

0 Hai Nguyen, et al. ∙

∙ 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...

0 Pulong Ma, et al. ∙

∙ 12/31/2012

Autonomously Learning to Visually Detect Where Manipulation Will Succeed

Visual features can help predict if a manipulation behavior will succeed...

0 Hai Nguyen, et al. ∙

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