91 citations · 182 across the 11 of their papers we have counts for
5 papers · 1 filter
Deep Reinforcement Learning for Real-Time Optimization of Pumps in Water Distribution Systems
Gergely Hajgató, György Paál, Bálint Gyires-Tóth
Real-time control of pumps can be an infeasible task in water distribution systems (WDSs) because the calculation to find the optimal pump speeds is resource-intensive. The computa…
Predicting the flow field in a U-bend with deep neural networks
Gergely Hajgató, Bálint Gyires-Tóth, György Paál
This paper describes a study based on computational fluid dynamics (CFD) and deep neural networks that focusing on predicting the flow field in differently distorted U-shaped pipes…
Robust Reinforcement Learning-based Autonomous Driving Agent for Simulation and Real World
Péter Almási, Róbert Moni, Bálint Gyires-Tóth
Deep Reinforcement Learning (DRL) has been successfully used to solve different challenges, e.g. complex board and computer games, recently. However, solving real-world robotics ta…
Self-Attention Networks for Intent Detection
Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth
Self-attention networks (SAN) have shown promising performance in various Natural Language Processing (NLP) scenarios, especially in machine translation. One of the main points of…
Transformer based Grapheme-to-Phoneme Conversion
Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth
Attention mechanism is one of the most successful techniques in deep learning based Natural Language Processing (NLP). The transformer network architecture is completely based on a…