Zobrazeno 1 - 10
of 95 820
pro vyhledávání: '"P. Gerhard"'
Symbolic integration is a fundamental problem in mathematics: we consider how machine learning may be used to optimise this task in a Computer Algebra System (CAS). We train transformers that predict whether a particular integration method will be su
Externí odkaz:
http://arxiv.org/abs/2410.23948
The integration of artificial intelligence into business processes has significantly enhanced decision-making capabilities across various industries such as finance, healthcare, and retail. However, explaining the decisions made by these AI systems p
Externí odkaz:
http://arxiv.org/abs/2410.20873
Autor:
Bošnjak, Domagoj, Schussnig, Richard, Ranftl, Sascha, Holzapfel, Gerhard A., Fries, Thomas-Peter
In the context of numerical simulations of the vascular system, local geometric uncertainties have not yet been examined in sufficient detail due to model complexity and the associated large numerical effort. Such uncertainties are related to geometr
Externí odkaz:
http://arxiv.org/abs/2410.19472
Autor:
Lahmeri, Mohamed-Amine, Mustieles-Pérez, Víctor, Vossiek, Martin, Krieger, Gerhard, Schober, Robert
In this paper, we study the optimization of the sensing accuracy of unmanned aerial vehicle (UAV)-based dual-baseline interferometric synthetic aperture radar (InSAR) systems. A swarm of three UAV-synthetic aperture radar (SAR) systems is deployed to
Externí odkaz:
http://arxiv.org/abs/2410.18848
Grasping is a fundamental skill in robotics with diverse applications across medical, industrial, and domestic domains. However, current approaches for predicting valid grasps are often tailored to specific grippers, limiting their applicability when
Externí odkaz:
http://arxiv.org/abs/2410.18835
Perceiving the environment via cameras is crucial for Reinforcement Learning (RL) in robotics. While images are a convenient form of representation, they often complicate extracting important geometric details, especially with varying geometries or d
Externí odkaz:
http://arxiv.org/abs/2410.18800
Autor:
Karwounopoulos, Johannes, Bieniek, Mateusz, Wu, Zhiyi, Baskerville, Adam L., Koenig, Gerhard, Cossins, Benjamin P., Wood, Geoffrey P. F.
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several ti
Externí odkaz:
http://arxiv.org/abs/2410.16818
Autor:
Pasqualato, G., Ansari, S., Heines, J. S., Modamio, V., Görgen, A., Korten, W., Ljungvall, J., Clément, E., Dudouet, J., Lemasson, A., Rodríguez, T. R., Allmond, J. M., Arici, T., Beckmann, K. S., Bruce, A. M., Doherty, D., Esmaylzadeh, A., Gamba, E. R., Gerhard, L., Gerl, J., Georgiev, G., Ivanova, D. P., Jolie, J., Kim, Y. -H., Knafla, L., Korichi, A., Koseoglou, P., Labiche, M., Lalkovski, S., Lauritsen, T., Li, H. -J., Pedersen, L. G., Pietri, S., Ralet, D., Regis, J. M., Rudigier, M., Saha, S., Sahin, E., Siem, S., Singh, P., öderström, P. -A., Theisen, C., Tornyi, T., Vandebrouck, M., Witt, W., Zielińska, M., Barrientos, D., Bednarczyk, P., Benzoni, G., Boston, A. J., Boston, H. C., Bracco, A., Cederwall, B, Ciemala, M., de France, G., Domingo-Pardo, C., Eberth, J., Gadea, A., González, V., Gottardo, A., Harkness-Brennan, L. J., Hess, H., Judson, D. S., Jungclaus, A., Lenzi, S. M., Leoni, S., Menegazzo, R., Mengoni, D., Michelagnoli, C., Napoli, D. R., Nyberg, J., Podolyak, Zs., Pullia, A., Recchia, F., Reiter, P., Rezynkina, K., Salsac, M. D., Sanchis, E., Şenyiğit, M., Siciliano, M., Simpson, J., Sohler, D., Stezowski, O., Valiente-Dobón, J. J., Verney, D.
Publikováno v:
Eur. Phys. J. A (2023) 59:276
The Zirconium (Z = 40) isotopic chain has attracted interest for more than four decades. The abrupt lowering of the energy of the first $2^+$ state and the increase in the transition strength B(E2; $2_1^\rightarrow 0_1^+$ going from $^{98}$Zr to $^{1
Externí odkaz:
http://arxiv.org/abs/2410.17004
Autor:
Wolf, Daniel, Payer, Tristan, Lisson, Catharina Silvia, Lisson, Christoph Gerhard, Beer, Meinrad, Götz, Michael, Ropinski, Timo
Publikováno v:
Computers in Biology and Medicine, Volume 183, 2024
Self-supervised pre-training of deep learning models with contrastive learning is a widely used technique in image analysis. Current findings indicate a strong potential for contrastive pre-training on medical images. However, further research is nec
Externí odkaz:
http://arxiv.org/abs/2410.14524
Finding efficient routes for data packets is an essential task in computer networking. The optimal routes depend greatly on the current network topology, state and traffic demand, and they can change within milliseconds. Reinforcement Learning can he
Externí odkaz:
http://arxiv.org/abs/2410.10377