Zobrazeno 1 - 10
of 25 328
pro vyhledávání: '"Schoen AN"'
Since neural networks can make wrong predictions even with high confidence, monitoring their behavior at runtime is important, especially in safety-critical domains like autonomous driving. In this paper, we combine ideas from previous monitoring app
Externí odkaz:
http://arxiv.org/abs/2410.06051
Capturing images using multispectral camera arrays has gained importance in medical, agricultural and environmental processes. However, using all available spectral bands is infeasible and produces much data, while only a fraction is needed for a giv
Externí odkaz:
http://arxiv.org/abs/2410.02001
For run sizes that are a multiple of four, the literature offers many two-level designs that are D- and A-optimal for the main-effects model and minimize the aliasing between main effects and interaction effects and among interaction effects. For run
Externí odkaz:
http://arxiv.org/abs/2409.13336
Diffusion models have achieved remarkable progress in generative modelling, particularly in enhancing image quality to conform to human preferences. Recently, these models have also been applied to low-level computer vision for photo-realistic image
Externí odkaz:
http://arxiv.org/abs/2409.10353
Generative diffusions are a powerful class of Monte Carlo samplers that leverage bridging Markov processes to approximate complex, high-dimensional distributions, such as those found in image processing and language models. Despite their success in t
Externí odkaz:
http://arxiv.org/abs/2409.09650
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