Bálint Gyires-Tóth

39 papers A 1B 3C 2Misc 2Journal 23Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Exploring joint embedding predictive architectures for pretraining convolutional neural networks. Comput. Vis. Image Underst. András Kalapos, Bálint Gyires-Tóth
2025	B	`conf`	Advancing Deep-Learning in NLP: From Network Logs to Text Classification. NOMS Lívia Réka Ónozó, Bálint Gyires-Tóth
2025	J	`jnl`	Explainable GNN-Based Approach to Fault Forecasting in Cloud Service Debugging. IEEE Trans. Netw. Serv. Manag. Dániel Unyi, Erno Rigó, Bálint Gyires-Tóth, Róbert Lovas
2025	J	`jnl`	Self-supervised domain transfer for reinforcement learning-based autonomous driving agent. Expert Syst. Appl. Róbert Moni, Bálint Gyires-Tóth
2025	—	`conf`	Semi-Supervised Learning for Loan Default Prediction: Leveraging Unlabeled Data from Time-Aware Splits. CAI Dániel Unyi, Bálint Gyires-Tóth
2024	C	`conf`	CNN-JEPA: Self-Supervised Pretraining Convolutional Neural Networks Using Joint Embedding Predictive Architecture. ICMLA András Kalapos, Bálint Gyires-Tóth
2024	J	`jnl`	CNN-JEPA: Self-Supervised Pretraining Convolutional Neural Networks Using Joint Embedding Predictive Architecture. CoRR András Kalapos, Bálint Gyires-Tóth
2024	J	`jnl`	Leveraging LLMs for Financial News Analysis and Macroeconomic Indicator Nowcasting. IEEE Access Lívia Réka Ónozó, Frigyes Viktor Arthur, Bálint Gyires-Tóth
2024	—	`conf`	Self-Supervised Pretraining for Cortical Surface Analysis. MIUA (1) Dániel Unyi, Bálint Gyires-Tóth
2024	C	`conf`	Whitening Consistently Improves Self-Supervised Learning. ICMLA András Kalapos, Bálint Gyires-Tóth
2024	J	`jnl`	Whitening Consistently Improves Self-Supervised Learning. CoRR András Kalapos, Bálint Gyires-Tóth
2023	J	`jnl`	Experiences With Deep Learning Enhanced Steering Mechanisms for Debugging of Fundamental Cloud Services. IEEE Access Róbert Lovas, Erno Rigó, Dániel Unyi, Bálint Gyires-Tóth
2023	—	`conf`	Language of the Market: NLP-Driven Sentiment Analysis of Hungarian Economy. CogInfoCom Frigyes Viktor Arthur, Bálint Gyires-Tóth, Máté Imre Debreczeni, Lívia Réka Ónozó
2023	J	`jnl`	Position control of an acoustic cavitation bubble by reinforcement learning. CoRR Kálmán Klapcsik, Bálint Gyires-Tóth, Juan Manuel Rosselló, Ferenc Hegedüs
2022	J	`jnl`	Improving Self-Supervised Learning-based MOS Prediction Networks. CoRR Bálint Gyires-Tóth, Csaba Zainkó
2022	—	`conf`	Neurodevelopmental Phenotype Prediction: A State-of-the-Art Deep Learning Model. ML4H@NeurIPS Dániel Unyi, Bálint Gyires-Tóth
2022	J	`jnl`	Neurodevelopmental Phenotype Prediction: A State-of-the-Art Deep Learning Model. CoRR Dániel Unyi, Bálint Gyires-Tóth
2022	J	`jnl`	PredMaX: Predictive maintenance with explainable deep convolutional autoencoders. Adv. Eng. Informatics Gergely Hajgató, Richárd Wéber, Botond Szilágyi, Balázs Tóthpál, Bálint Gyires-Tóth, Csaba Hos
2022	J	`jnl`	Self-Supervised Pretraining for 2D Medical Image Segmentation. CoRR András Kalapos, Bálint Gyires-Tóth
2022	—	`conf`	Self-supervised Pretraining for 2D Medical Image Segmentation. ECCV Workshops (7) András Kalapos, Bálint Gyires-Tóth
2022	—	`conf`	Utility of Equivariant Message Passing in Cortical Mesh Segmentation. MIUA Dániel Unyi, Ferdinando Insalata, Petar Velickovic, Bálint Gyires-Tóth
2022	J	`jnl`	Utility of Equivariant Message Passing in Cortical Mesh Segmentation. CoRR Dániel Unyi, Ferdinando Insalata, Petar Velickovic, Bálint Gyires-Tóth
2021	J	`jnl`	Distance assessment and analysis of high-dimensional samples using variational autoencoders. Inf. Sci. Marco Henrique de Almeida Inácio, Rafael Izbicki, Bálint Gyires-Tóth
2021	J	`jnl`	Reconstructing nodal pressures in water distribution systems with graph neural networks. CoRR Gergely Hajgató, Bálint Gyires-Tóth, György Paál
2021	Misc	`conf`	Scalable Graph Convolutional Variational Autoencoders. SACI Dániel Unyi, Bálint Gyires-Tóth
2020	J	`jnl`	Deep Reinforcement Learning for Real-Time Optimization of Pumps in Water Distribution Systems. CoRR Gergely Hajgató, György Paál, Bálint Gyires-Tóth
2020	—	`conf`	GPU Accelerated Data Preparation for Limit Order Book Modeling. LOD (1) Viktor Burján, Bálint Gyires-Tóth
2020	J	`jnl`	Predicting the flow field in a U-bend with deep neural networks. CoRR Gergely Hajgató, Bálint Gyires-Tóth, György Paál
2020	B	`conf`	Robust Reinforcement Learning-based Autonomous Driving Agent for Simulation and Real World. IJCNN Péter Almási, Róbert Moni, Bálint Gyires-Tóth
2020	J	`jnl`	Robust Reinforcement Learning-based Autonomous Driving Agent for Simulation and Real World. CoRR Péter Almási, Róbert Moni, Bálint Gyires-Tóth
2020	J	`jnl`	Self-Attention Networks for Intent Detection. CoRR Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth
2020	J	`jnl`	Transformer based Grapheme-to-Phoneme Conversion. CoRR Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth
2019	J	`jnl`	Distance Assessment and Hypothesis Testing of High-Dimensional Samples using Variational Autoencoders. CoRR Marco Henrique de Almeida Inácio, Rafael Izbicki, Bálint Gyires-Tóth
2019	Misc	`conf`	Self-Attention Networks for Intent Detection. RANLP Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth
2019	—	`conf`	Stochastic Weight Matrix-Based Regularization Methods for Deep Neural Networks. LOD Patrik Reizinger, Bálint Gyires-Tóth
2019	J	`jnl`	Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks. CoRR Patrik Reizinger, Bálint Gyires-Tóth
2019	A	`conf`	Transformer Based Grapheme-to-Phoneme Conversion. INTERSPEECH Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth
2019	B	`conf`	Utilizing Deep Learning for Mobile Telecommunications Network Management. IM Bálint Gyires-Tóth, Pál Varga, Tamas Tothfalusi
2018	J	`jnl`	Text normalization with convolutional neural networks. Int. J. Speech Technol. Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth