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pro vyhledávání: '"Schoen A"'
Uncertainty estimation is a necessary component when implementing AI in high-risk settings, such as autonomous cars, medicine, or insurances. Large Language Models (LLMs) have seen a surge in popularity in recent years, but they are subject to halluc
Externí odkaz:
http://arxiv.org/abs/2409.02976
Safe Bayesian optimization (BO) algorithms promise to find optimal control policies without knowing the system dynamics while at the same time guaranteeing safety with high probability. In exchange for those guarantees, popular algorithms require a s
Externí odkaz:
http://arxiv.org/abs/2409.01163
In this report we investigate the use of the Tustin neural network architecture (Tustin-Net) for the identification of a physical rotary inverse pendulum. This physics-based architecture is of particular interest as it builds on the known relationshi
Externí odkaz:
http://arxiv.org/abs/2408.12266
To advance formal verification of stochastic systems against temporal logic requirements for handling unknown dynamics, researchers have been designing data-driven approaches inspired by breakthroughs in the underlying machine learning techniques. As
Externí odkaz:
http://arxiv.org/abs/2407.21029
In this paper we introduce a new dataset containing instance segmentation masks for ten different categories of winter sports equipment, called WSESeg (Winter Sports Equipment Segmentation). Furthermore, we carry out interactive segmentation experime
Externí odkaz:
http://arxiv.org/abs/2407.09288
In many manufacturing settings, annotating data for machine learning and computer vision is costly, but synthetic data can be generated at significantly lower cost. Substituting the real-world data with synthetic data is therefore appealing for many
Externí odkaz:
http://arxiv.org/abs/2406.19175
Autor:
Kyriakoglou, Revekka, Pappa, Anna, He, Jilin, Schoen, Antoine, Laurens, Patricia, Vartampetian, Markarit, Laredo, Philippe, Kyriacopoulou, Tita
This paper presents the development of a lexicon centered on emerging concepts, focusing on non-technological innovation. It introduces a four-step methodology that combines human expertise, statistical analysis, and machine learning techniques to es
Externí odkaz:
http://arxiv.org/abs/2406.10253
Context: In agile transformations, there are many challenges such as alignment between agile practices and the organizational goals and strategies or issues with shifts in how work is organized and executed. One very important challenge but less cons
Externí odkaz:
http://arxiv.org/abs/2405.15066
Utilizing transformer architectures for semantic segmentation of high-resolution images is hindered by the attention's quadratic computational complexity in the number of tokens. A solution to this challenge involves decreasing the number of tokens t
Externí odkaz:
http://arxiv.org/abs/2405.14467
Given an unconditional diffusion model $\pi(x, y)$, using it to perform conditional simulation $\pi(x \mid y)$ is still largely an open question and is typically achieved by learning conditional drifts to the denoising SDE after the fact. In this wor
Externí odkaz:
http://arxiv.org/abs/2405.13794