Zobrazeno 1 - 10
of 13 142
pro vyhledávání: '"Hamm, P."'
We present an algorithm for growing the denominator $r$ polygons containing a fixed number of lattice points and enumerate such polygons containing few lattice points for small $r$. We describe the Ehrhart quasi-polynomial of a rational polygon in te
Externí odkaz:
http://arxiv.org/abs/2411.19183
Current AI-assisted skin image diagnosis has achieved dermatologist-level performance in classifying skin cancer, driven by rapid advancements in deep learning architectures. However, unlike traditional vision tasks, skin images in general present un
Externí odkaz:
http://arxiv.org/abs/2409.09520
Parametrizing energy functions for ionic systems can be challenging. Here, the total energy function for an eutectic system consisting of water, SCN$^-$, K$^+$ and acetamide is improved vis-a-vis experimentally measured properties. Given the importan
Externí odkaz:
http://arxiv.org/abs/2408.07638
Through comprehensive data analysis, we demonstrate that a ${\chi}^{(2)}$-induced artifact, arising from imperfect balancing in the conventional electro-optic sampling (EOS) detection scheme, contributes significantly to the measured signal in 2D Ram
Externí odkaz:
http://arxiv.org/abs/2407.09243
AI-based diagnoses have demonstrated dermatologist-level performance in classifying skin cancer. However, such systems are prone to under-performing when tested on data from minority groups that lack sufficient representation in the training sets. Al
Externí odkaz:
http://arxiv.org/abs/2406.18375
Continual Test-Time Adaptation (CTTA) seeks to adapt a source pre-trained model to continually changing, unlabeled target domains. Existing TTA methods are typically designed for environments where domain changes occur sequentially and can struggle i
Externí odkaz:
http://arxiv.org/abs/2406.10737
Vision Transformers (ViTs) have demonstrated remarkable capabilities in learning representations, but their performance is compromised when applied to unseen domains. Previous methods either engage in prompt learning during the training phase or modi
Externí odkaz:
http://arxiv.org/abs/2407.09498
Gauging the performance of ML models on data from unseen domains at test-time is essential yet a challenging problem due to the lack of labels in this setting. Moreover, the performance of these models on in-distribution data is a poor indicator of t
Externí odkaz:
http://arxiv.org/abs/2405.01451
Autor:
Bell, Brian, Geyer, Michael, Glickenstein, David, Hamm, Keaton, Scheidegger, Carlos, Fernandez, Amanda, Moore, Juston
There are a number of hypotheses underlying the existence of adversarial examples for classification problems. These include the high-dimensionality of the data, high codimension in the ambient space of the data manifolds of interest, and that the st
Externí odkaz:
http://arxiv.org/abs/2404.08069
Social distance games have been extensively studied as a coalition formation model where the utilities of agents in each coalition were captured using a utility function $u$ that took into account distances in a given social network. In this paper, w
Externí odkaz:
http://arxiv.org/abs/2312.07632