Zobrazeno 1 - 10
of 5 939
pro vyhledávání: '"Abram, P."'
In this chapter, we investigate the energy spectra as well as the bulk and surface states in a two-dimensional system composed of a coupled stack of one-dimensional dimerized chains in the presence of an external magnetic field. Specifically, we anal
Externí odkaz:
http://arxiv.org/abs/2409.07383
We measure the performance of in-context learning as a function of task novelty and difficulty for open and closed questions. For that purpose, we created a novel benchmark consisting of hard scientific questions, each paired with a context of variou
Externí odkaz:
http://arxiv.org/abs/2407.02028
Autor:
Abram, Antoine, Hivert, Florent, Mitchell, James D., Novelli, Jean-Christophe, Tsalakou, Maria
Publikováno v:
EPTCS 403, 2024, pp. 12-17
In this paper we describe the quotients of several plactic-like monoids by the least congruences containing the relations $a^{\sigma(a)} = a$ with $\sigma(a)\ge 2$ for every generator $a$. The starting point for this description is the recent paper o
Externí odkaz:
http://arxiv.org/abs/2406.16387
The sparse dictionary coding framework represents signals as a linear combination of a few predefined dictionary atoms. It has been employed for images, time series, graph signals and recently for 2-way (or 2D) spatio-temporal data employing jointly
Externí odkaz:
http://arxiv.org/abs/2406.06960
Symmetry detection can improve various machine learning tasks. In the context of continuous symmetry detection, current state of the art experiments are limited to detecting affine transformations. Under the manifold assumption, we outline a framewor
Externí odkaz:
http://arxiv.org/abs/2406.03619
We use numerical simulations to demonstrate a local rheology for sheared, vibrated granular flows. We consider a granular assembly that is subjected to simple shear and harmonic vibration at the boundary. This configuration allows us to isolate the e
Externí odkaz:
http://arxiv.org/abs/2405.13236
Here we theoretically and computationally study the frequency dependence of phase speed and attenuation for marine sediments from the perspective of granular mechanics. We leverage recent theoretical insights from the granular physics community as we
Externí odkaz:
http://arxiv.org/abs/2405.06614
Autor:
Agrawal, Vikhyat, Kalmady, Sunil Vasu, Malipeddi, Venkataseetharam Manoj, Manthena, Manisimha Varma, Sun, Weijie, Islam, Saiful, Hindle, Abram, Kaul, Padma, Greiner, Russell
This research paper explores ways to apply Federated Learning (FL) and Differential Privacy (DP) techniques to population-scale Electrocardiogram (ECG) data. The study learns a multi-label ECG classification model using FL and DP based on 1,565,849 E
Externí odkaz:
http://arxiv.org/abs/2405.00725
Autor:
Williams, Ben, van Merriënboer, Bart, Dumoulin, Vincent, Hamer, Jenny, Triantafillou, Eleni, Fleishman, Abram B., McKown, Matthew, Munger, Jill E., Rice, Aaron N., Lillis, Ashlee, White, Clemency E., Hobbs, Catherine A. D., Razak, Tries B., Jones, Kate E., Denton, Tom
Machine learning has the potential to revolutionize passive acoustic monitoring (PAM) for ecological assessments. However, high annotation and compute costs limit the field's efficacy. Generalizable pretrained networks can overcome these costs, but h
Externí odkaz:
http://arxiv.org/abs/2404.16436
Understanding the characteristics of swarming autonomous agents is critical for defense and security applications. This article presents a study on using supervised neural network time series classification (NN TSC) to predict key attributes and tact
Externí odkaz:
http://arxiv.org/abs/2403.19572