Zobrazeno 1 - 10
of 9 492
pro vyhledávání: '"Seshadri, P A"'
In the context of cellular networks, users located at the periphery of cells are particularly vulnerable to substantial interference from neighbouring cells, which can be represented as a two-user interference channel. This study introduces two highl
Externí odkaz:
http://arxiv.org/abs/2410.19767
Autor:
Forero-Sánchez, Daniel, Rashkovetskyi, Michael, Alves, Otávio, de Mattia, Arnaud, Nadathur, Seshadri, Zarrouk, Pauline, Gil-Marín, Héctor, Ding, Zhejie, Yu, Jiaxi, Andrade, Uendert, Chen, Xinyi, Garcia-Quintero, Cristhian, Mena-Fernández, Juan, Ahlen, Steven, Bianchi, Davide, Brooks, David, Burtin, Etienne, Chaussidon, Edmond, Claybaugh, Todd, Cole, Shaun, de la Macorra, Axel, Vargas, Miguel Enriquez, Gaztañaga, Enrique, Gutierrez, Gaston, Honscheid, Klaus, Howlett, Cullan, Kisner, Theodore, Landriau, Martin, Guillou, Laurent Le, Levi, Michael, Miquel, Ramon, Moustakas, John, Palanque-Delabrouille, Nathalie, Percival, Will, Pérez-Ràfols, Ignasi, Ross, Ashley J., Rossi, Graziano, Sanchez, Eusebio, Schlegel, David, Schubnell, Michael, Seo, Hee-Jong, Sprayberry, David, Tarlé, Gregory, Magana, Mariana Vargas, Weaver, Benjamin Alan, Zou, Hu
The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full Shape, two approaches are usually considered. Firs
Externí odkaz:
http://arxiv.org/abs/2411.12027
Autor:
Verma, Sahil, Rassin, Royi, Das, Arnav, Bhatt, Gantavya, Seshadri, Preethi, Shah, Chirag, Bilmes, Jeff, Hajishirzi, Hannaneh, Elazar, Yanai
Text-to-image models are trained using large datasets collected by scraping image-text pairs from the internet. These datasets often include private, copyrighted, and licensed material. Training models on such datasets enables them to generate images
Externí odkaz:
http://arxiv.org/abs/2410.15002
The development of a "Large Airfoil Model (LAM)," a transformative approach for answering technical questions on airfoil aerodynamics, requires a vast dataset and a model to leverage it. To build this foundation, a novel probabilistic machine learnin
Externí odkaz:
http://arxiv.org/abs/2410.08392
Autor:
Seshadri, Amrit Diggavi
With the size and cost of large transformer-based language models growing, recently, there has been interest in shortcut casting of early transformer hidden-representations to final-representations for cheaper model inference. In particular, shortcut
Externí odkaz:
http://arxiv.org/abs/2409.14091
Macroscopic fundamental diagrams (MFDs) and related network traffic dynamics models have received both theoretical support and empirical validation with the emergence of new data collection technologies. However, the existence of well-defined MFD cur
Externí odkaz:
http://arxiv.org/abs/2409.12689
Modern music streaming services are heavily based on recommendation engines to serve content to users. Sequential recommendation -- continuously providing new items within a single session in a contextually coherent manner -- has been an emerging top
Externí odkaz:
http://arxiv.org/abs/2409.07367
We explore the use of FCNNs (Fully Connected Neural Networks) for designing end-to-end communication systems without taking any inspiration from existing classical communications models or error control coding. This work relies solely on the tools of
Externí odkaz:
http://arxiv.org/abs/2409.01129
Autor:
Seshadri, Ranjani
The phenomenon of Parametric Resonance (PR) is very well studied in classical systems with one of the textbook examples being the stabilization of a Kapitza's pendulum in the inverted configuration when the suspension point is oscillated vertically.
Externí odkaz:
http://arxiv.org/abs/2408.06228
Autor:
Chapman, Stephen D., Seshadri, Suparna, Lukens, Joseph M., Peters, Nicholas A., McKinney, Jason D., Weiner, Andrew M., Lu, Hsuan-Hao
We demonstrate nonlocal modulation of entangled photons with truly distributed RF clocks. Leveraging a custom radio-over-fiber (RFoF) system characterized via classical spectral interference, we validate its effectiveness for quantum networking by mu
Externí odkaz:
http://arxiv.org/abs/2407.17330