Bálint Gyires-Tóth

According to our database, Bálint Gyires-Tóth authored at least 25 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Whitening Consistently Improves Self-Supervised Learning.

András Kalapos, Bálint Gyires-Tóth

CoRR, 2024

CNN-JEPA: Self-Supervised Pretraining Convolutional Neural Networks Using Joint Embedding Predictive Architecture.

András Kalapos, Bálint Gyires-Tóth

CoRR, 2024

Leveraging LLMs for Financial News Analysis and Macroeconomic Indicator Nowcasting.

Lívia Réka Ónozó, Frigyes Viktor Arthur, Bálint Gyires-Tóth

IEEE Access, 2024

Self-Supervised Pretraining for Cortical Surface Analysis.

Dániel Unyi, Bálint Gyires-Tóth

Proceedings of the Medical Image Understanding and Analysis - 28th Annual Conference, 2024

2023

Position control of an acoustic cavitation bubble by reinforcement learning.

Kálmán Klapcsik, Bálint Gyires-Tóth, Juan Manuel Rosselló, Ferenc Hegedüs

CoRR, 2023

Experiences With Deep Learning Enhanced Steering Mechanisms for Debugging of Fundamental Cloud Services.

Róbert Lovas, Erno Rigó, Dániel Unyi, Bálint Gyires-Tóth

IEEE Access, 2023

Language of the Market: NLP-Driven Sentiment Analysis of Hungarian Economy.

Frigyes Viktor Arthur, Bálint Gyires-Tóth, Máté Imre Debreczeni, Lívia Réka Ónozó

Proceedings of the 14th IEEE International Conference on Cognitive Infocommunications, 2023

2022

Improving Self-Supervised Learning-based MOS Prediction Networks.

Bálint Gyires-Tóth, Csaba Zainkó

CoRR, 2022

PredMaX: Predictive maintenance with explainable deep convolutional autoencoders.

Gergely Hajgató, Richárd Wéber, Botond Szilágyi, Balázs Tóthpál, Bálint Gyires-Tóth, Csaba Hos

Adv. Eng. Informatics, 2022

Neurodevelopmental Phenotype Prediction: A State-of-the-Art Deep Learning Model.

Dániel Unyi, Bálint Gyires-Tóth

Proceedings of the Machine Learning for Health, 2022

Utility of Equivariant Message Passing in Cortical Mesh Segmentation.

Dániel Unyi, Ferdinando Insalata, Petar Velickovic, Bálint Gyires-Tóth

Proceedings of the Medical Image Understanding and Analysis - 26th Annual Conference, 2022

Self-supervised Pretraining for 2D Medical Image Segmentation.

András Kalapos, Bálint Gyires-Tóth

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2021

Distance assessment and analysis of high-dimensional samples using variational autoencoders.

Marco Henrique de Almeida Inácio, Rafael Izbicki, Bálint Gyires-Tóth

Inf. Sci., 2021

Reconstructing nodal pressures in water distribution systems with graph neural networks.

Gergely Hajgató, Bálint Gyires-Tóth, György Paál

CoRR, 2021

Scalable Graph Convolutional Variational Autoencoders.

Dániel Unyi, Bálint Gyires-Tóth

Proceedings of the 15th IEEE International Symposium on Applied Computational Intelligence and Informatics, 2021

2020

Deep Reinforcement Learning for Real-Time Optimization of Pumps in Water Distribution Systems.

Gergely Hajgató, György Paál, Bálint Gyires-Tóth

CoRR, 2020

Predicting the flow field in a U-bend with deep neural networks.

Gergely Hajgató, Bálint Gyires-Tóth, György Paál

CoRR, 2020

GPU Accelerated Data Preparation for Limit Order Book Modeling.

Viktor Burján, Bálint Gyires-Tóth

Proceedings of the Machine Learning, Optimization, and Data Science, 2020

Robust Reinforcement Learning-based Autonomous Driving Agent for Simulation and Real World.

Péter Almási, Róbert Moni, Bálint Gyires-Tóth

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Distance Assessment and Hypothesis Testing of High-Dimensional Samples using Variational Autoencoders.

Marco Henrique de Almeida Inácio, Rafael Izbicki, Bálint Gyires-Tóth

CoRR, 2019

Self-Attention Networks for Intent Detection.

Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth

Proceedings of the International Conference on Recent Advances in Natural Language Processing, 2019

Stochastic Weight Matrix-Based Regularization Methods for Deep Neural Networks.

Patrik Reizinger, Bálint Gyires-Tóth

Proceedings of the Machine Learning, Optimization, and Data Science, 2019

Transformer Based Grapheme-to-Phoneme Conversion.

Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth

Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

Utilizing Deep Learning for Mobile Telecommunications Network Management.

Bálint Gyires-Tóth, Pál Varga, Tamas Tothfalusi

Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management, 2019

2018

Text normalization with convolutional neural networks.

Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth

Int. J. Speech Technol., 2018