Zobrazeno 1 - 10
of 11 795
pro vyhledávání: '"Bak, P. A."'
Text-to-speech (TTS) systems that scale up the amount of training data have achieved significant improvements in zero-shot speech synthesis. However, these systems have certain limitations: they require a large amount of training data, which increase
Externí odkaz:
http://arxiv.org/abs/2410.03192
Autor:
Susarla, S. C., Chalumeau, A., Tiburzi, C., Keane, E. F., Verbiest, J. P. W., Hazboun, J. S., Krishnakumar, M. A., Iraci, F., Shaifullah, G. M., Golden, A., Nielsen, A. S. Bak, Donner, J., Grießmeier, J. M., Keith, M. J., Osłowski, S., Porayko, N. K., Serylak, M., Anderson, J. M., Brüggen, M., Ciardi, B., Dettmar, R. J., Hoeft, M., Künsemöller, J., Schwarz, D., Vocks, C.
High-precision pulsar timing is highly dependent on precise and accurate modeling of any effects that impact the data. It was shown that commonly used Solar Wind models do not accurately account for variability in the amplitude of the Solar wind on b
Externí odkaz:
http://arxiv.org/abs/2409.09838
Mid-air navigation offers a method of aerial travel that mitigates the constraints associated with continuous navigation. A mid-air selection technique is essential to enable such navigation. In this paper, we consider four variations of intersection
Externí odkaz:
http://arxiv.org/abs/2408.15199
In this study, we calculate the $m-1$ correction to the reflected entropy for two adjacent intervals on a half-infinite line within the AdS$_3$/BCFT$_2$ framework, where $m$ is a Renyi index for a canonical purification. We utilize the doubling trick
Externí odkaz:
http://arxiv.org/abs/2408.14034
Accessing machine learning models through remote APIs has been gaining prevalence following the recent trend of scaling up model parameters for increased performance. Even though these models exhibit remarkable ability, detecting out-of-distribution
Externí odkaz:
http://arxiv.org/abs/2408.10107
ALTBI: Constructing Improved Outlier Detection Models via Optimization of Inlier-Memorization Effect
Outlier detection (OD) is the task of identifying unusual observations (or outliers) from a given or upcoming data by learning unique patterns of normal observations (or inliers). Recently, a study introduced a powerful unsupervised OD (UOD) solver b
Externí odkaz:
http://arxiv.org/abs/2408.09791
Autor:
Bläsius, Thomas, von der Heydt, Jean-Pierre, Kisfaludi-Bak, Sándor, Wilhelm, Marcus, van Wordragen, Geert
We consider intersection graphs of disks of radius $r$ in the hyperbolic plane. Unlike the Euclidean setting, these graph classes are different for different values of $r$, where very small $r$ corresponds to an almost-Euclidean setting and $r \in \O
Externí odkaz:
http://arxiv.org/abs/2407.09362
While machines learn from existing corpora, humans have the unique capability to establish and accept new language systems. This makes human form unique language systems within social groups. Aligning with this, we focus on a gap remaining in address
Externí odkaz:
http://arxiv.org/abs/2407.07413
We consider a time-dependent $\mathcal{O}(1/G)$ deformation of pure de Sitter (dS) space in dS gravity coupled to a massless scalar field. It is the dS counterpart of the AdS Janus deformation and interpolates two asymptotically dS spaces in the far
Externí odkaz:
http://arxiv.org/abs/2407.04316
As mental health issues globally escalate, there is a tremendous need for advanced digital support systems. We introduce MentalAgora, a novel framework employing large language models enhanced by interaction between multiple agents for tailored menta
Externí odkaz:
http://arxiv.org/abs/2407.02736