Zobrazeno 1 - 10
of 33 029
pro vyhledávání: '"Marten, A."'
Bubble curtains are widely used to protect marine life from exposure to noise during offshore construction. However, operating a bubble curtain is costly. Therefore optimizing the acoustic effect of the available air is important. An interesting appr
Externí odkaz:
http://arxiv.org/abs/2410.14415
Timing control while preserving determinism is often a key requirement for ensuring the safety and correctness of distributed cyber-physical systems (CPS). Discrete-event (DE) systems provide a suitable model of computation (MoC) for time-sensitive d
Externí odkaz:
http://arxiv.org/abs/2410.06454
In this paper, we study Artinian and Noetherian properties in vector lattices and provide a concrete representation of these spaces. Furthermore, we describe for which Archimedean uniformly complete vector lattices every decreasing sequence of prime
Externí odkaz:
http://arxiv.org/abs/2410.03329
Recent advancements in generative modeling, particularly diffusion models, have opened new directions for time series modeling, achieving state-of-the-art performance in forecasting and synthesis. However, the reliance of diffusion-based models on a
Externí odkaz:
http://arxiv.org/abs/2410.03024
Autor:
Reichlin, Alfredo, Tegnér, Gustaf, Vasco, Miguel, Yin, Hang, Björkman, Mårten, Kragic, Danica
Given a finite set of sample points, meta-learning algorithms aim to learn an optimal adaptation strategy for new, unseen tasks. Often, this data can be ambiguous as it might belong to different tasks concurrently. This is particularly the case in me
Externí odkaz:
http://arxiv.org/abs/2410.01476
Autor:
Fouesneau, Morgan, Momcheva, Ivelina G., Chadayammuri, Urmila, Demianenko, Mariia, Dumont, Antoine, Hviding, Raphael E., Kahle, K. Angelique, Pulatova, Nadiia, Rajpoot, Bhavesh, Scheuck, Marten B., Seeburger, Rhys, Semenov, Dmitry, Villaseñor, Jaime I.
ChatGPT and other state-of-the-art large language models (LLMs) are rapidly transforming multiple fields, offering powerful tools for a wide range of applications. These models, commonly trained on vast datasets, exhibit human-like text generation ca
Externí odkaz:
http://arxiv.org/abs/2409.20252
Robotic systems for manipulation tasks are increasingly expected to be easy to configure for new tasks or unpredictable environments, while keeping a transparent policy that is readable and verifiable by humans. We propose the method BEhavior TRee eX
Externí odkaz:
http://arxiv.org/abs/2409.13356
Kernel image regression methods have shown to provide excellent efficiency in many image processing task, such as image and light-field compression, Gaussian Splatting, denoising and super-resolution. The estimation of parameters for these methods fr
Externí odkaz:
http://arxiv.org/abs/2409.10101
Mixed multinomial logits are discrete mixtures introduced several decades ago to model the probability of choosing an attribute from $p$ possible candidates, in heterogeneous populations. The model has recently attracted attention in the AI literatur
Externí odkaz:
http://arxiv.org/abs/2409.09903
A catalytic machine is a model of computation where a traditional space-bounded machine is augmented with an additional, significantly larger, "catalytic" tape, which, while being available as a work tape, has the caveat of being initialized with an
Externí odkaz:
http://arxiv.org/abs/2409.05046