Zobrazeno 1 - 10
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pro vyhledávání: '"A. Farsang"'
Dynamic Vision Sensors (DVS), offer a unique advantage in control applications, due to their high temporal resolution, and asynchronous event-based data. Still, their adoption in machine learning algorithms remains limited. To address this gap, and p
Externí odkaz:
http://arxiv.org/abs/2409.18038
We introduce liquid-resistance liquid-capacitance neural networks (LRCs), a neural-ODE model which considerably improve the generalization, accuracy, and biological plausibility of electrical equivalent circuits (EECs), liquid time-constant networks
Externí odkaz:
http://arxiv.org/abs/2403.08791
Contextual bandits with average-case statistical guarantees are inadequate in risk-averse situations because they might trade off degraded worst-case behaviour for better average performance. Designing a risk-averse contextual bandit is challenging b
Externí odkaz:
http://arxiv.org/abs/2210.13573
Autor:
János Nemcsik, Johanna Takács, Dorottya Pásztor, Csaba Farsang, Attila Simon, Dénes Páll, Péter Torzsa, Szilveszter Dolgos, Akos Koller, Norbert Habony, Zoltán Járai
Publikováno v:
Blood Pressure, Vol 33, Iss 1 (2024)
AbstractPurpose Hypertension is a major public health problem, thus, its timely and appropriate diagnosis and management are crucial for reducing cardiovascular morbidity and mortality. The aim of the new Hungarian Hypertension Registry is to evaluat
Externí odkaz:
https://doaj.org/article/72147fb7c77045f2b61b3453349970a2
Publikováno v:
In Trends in Analytical Chemistry July 2024 176
Autor:
Farsang, Mónika, Szegletes, Luca
Publikováno v:
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI), 2021, pp. 000521-000526
Proximal Policy Optimization (PPO) is among the most widely used algorithms in reinforcement learning, which achieves state-of-the-art performance in many challenging problems. The keys to its success are the reliable policy updates through the clipp
Externí odkaz:
http://arxiv.org/abs/2102.10456
Autor:
Farsang, Mónika, Szegletes, Luca
Publikováno v:
Proceedings of the Automation and Applied Computer Science Workshop 2021
An in-depth understanding of the particular environment is crucial in reinforcement learning (RL). To address this challenge, the decision-making process of a mobile collaborative robotic assistant modeled by the Markov decision process (MDP) framewo
Externí odkaz:
http://arxiv.org/abs/2102.10447
Publikováno v:
In Journal of Pharmaceutical and Biomedical Analysis 20 January 2024 238
Publikováno v:
Environmental Sciences Europe, Vol 35, Iss 1, Pp 1-13 (2023)
Abstract Background Plastic greenhouse farming has become widespread worldwide because of its contributions to various agricultural production. However, it also generates plastic waste in large quantities and pollutes farmlands. Contrary to studies o
Externí odkaz:
https://doaj.org/article/e57bcd539555489395df103ccb3f1546
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