Zobrazeno 1 - 10
of 262
pro vyhledávání: '"68T07 (Primary)"'
We introduce two convolutional neural network (CNN) architectures, inspired by the Merriman-Bence-Osher (MBO) algorithm and by cellular automatons, to model and learn threshold dynamics for front evolution from video data. The first model, termed the
Externí odkaz:
http://arxiv.org/abs/2412.09079
In the rapidly evolving financial sector, the accurate and timely interpretation of market news is essential for stakeholders needing to navigate unpredictable events. This paper introduces FANAL (Financial Activity News Alerting Language Modeling Fr
Externí odkaz:
http://arxiv.org/abs/2412.03527
Autor:
Huang, Changcun
A neural network with one hidden layer or a two-layer network (regardless of the input layer) is the simplest feedforward neural network, whose mechanism may be the basis of more general network architectures. However, even to this type of simple arc
Externí odkaz:
http://arxiv.org/abs/2411.06728
Autor:
Boulaimen, Youssef, Fossi, Gabriele, Outemzabet, Leila, Jeanray, Nathalie, Levenets, Oleksandr, Gerart, Stephane, Vachenc, Sebastien, Raieli, Salvatore, Giemza, Joanna
The classification of genetic variants, particularly Variants of Uncertain Significance (VUS), poses a significant challenge in clinical genetics and precision medicine. Large Language Models (LLMs) have emerged as transformative tools in this realm.
Externí odkaz:
http://arxiv.org/abs/2411.05055
We propose an effective method for inserting adapters into text-to-image foundation models, which enables the execution of complex downstream tasks while preserving the generalization ability of the base model. The core idea of this method is to opti
Externí odkaz:
http://arxiv.org/abs/2410.22901
Studying the interplay between the geometry of the loss landscape and the optimization trajectories of simple neural networks is a fundamental step for understanding their behavior in more complex settings. This paper reveals the presence of topologi
Externí odkaz:
http://arxiv.org/abs/2410.14837
Autor:
Nordenfors, Oskar, Flinth, Axel
Recently, it was proved that group equivariance emerges in ensembles of neural networks as the result of full augmentation in the limit of infinitely wide neural networks (neural tangent kernel limit). In this paper, we extend this result significant
Externí odkaz:
http://arxiv.org/abs/2410.01452
Recent years have seen significant growth of quantum technologies, and specifically quantum sensing, both in terms of the capabilities of advanced platforms and their applications. One of the leading platforms in this context is nitrogen-vacancy (NV)
Externí odkaz:
http://arxiv.org/abs/2409.12820
Autor:
Khandan, Shokooh
Hand gesture recognition systems have yielded many exciting advancements in the last decade and become more popular in HCI (human-computer interaction) with several application areas, which spans from safety and security applications to automotive fi
Externí odkaz:
http://arxiv.org/abs/2410.02771
Transformer models are increasingly prevalent in various applications, yet our understanding of their internal workings remains limited. This paper investigates the modularity and task specialization of neurons within transformer architectures, focus
Externí odkaz:
http://arxiv.org/abs/2408.17324