Zobrazeno 1 - 10
of 15 939
pro vyhledávání: '"Unal P"'
Autor:
Johansen Stein Tore, Unal Perin, Albayrak Özlem, Ikonen Enso, Linnestad Kasper J., Jawahery Sudi, Srivastava Akhilesh K., Løvfall Bjørn Tore
Publikováno v:
Open Engineering, Vol 13, Iss 1, Pp p. 1-8 (2023)
In a Europe that is undergoing digital transformation, the COGNITWIN project is contributing to accelerate the transformation and introduce Industry 4.0 to the European process industries. The opportunities here can be illustrated by the SPIRE 2050 V
Externí odkaz:
https://doaj.org/article/ddda392bac1a48a89546958f8f0f0d2e
Autor:
Agazie, Gabriella, Anumarlapudi, Akash, Archibald, Anne M., Arzoumanian, Zaven, Baier, Jeremy G., Baker, Paul T., Becsy, Bence, Blecha, Laura, Brazier, Adam, Brook, Paul R., Burke-Spolaor, Sarah, Casey-Clyde, J. Andrew, Charisi, Maria, Chatterjee, Shami, Cohen, Tyler, Cordes, James M., Cornish, Neil J., Crawford, Fronefield, Cromartie, H. Thankful, Crowter, Kathryn, DeCesar, Megan E., Demorest, Paul B., Deng, Heling, Dey, Lankeswar, Dolch, Timothy, Ferrara, Elizabeth C., Fiore, William, Fonseca, Emmanuel, Freedman, Gabriel E., Gardiner, Emiko C., Garver-Daniels, Nate, Gentile, Peter A., Gersbach, Kyle A., Glaser, Joseph, Good, Deborah C., Guertin, Lydia, Gultekin, Kayhan, Hazboun, Jeffrey S., Jennings, Ross J., Johnson, Aaron D., Jones, Megan L., Kaiser, Andrew R., Kaplan, David L., Kelley, Luke Zoltan, Kerr, Matthew, Key, Joey S., Laal, Nima, Lam, Michael T., Lamb, William G., Larsen, Bjorn, Lazio, T. Joseph W., Lewandowska, Natalia, Liu, Tingting, Lorimer, Duncan R., Luo, Jing, Lynch, Ryan S., Ma, Chung-Pei, Madison, Dustin R., McEwen, Alexander, McKee, James W., McLaughlin, Maura A., McMann, Natasha, Meyers, Bradley W., Meyers, Patrick M., Middleton, Hannah, Mingarelli, Chiara M. F., Mitridate, Andrea, Moore, Christopher J., Ng, Cherry, Nice, David J., Ocker, Stella Koch, Olum, Ken D., Pennucci, Timothy T., Perera, Benetge B. P., Pol, Nihan S., Radovan, Henri A., Ransom, Scott M., Ray, Paul S., Romano, Joseph D., Runnoe, Jessie C., Saffer, Alexander, Sardesai, Shashwat C., Schmiedekamp, Ann, Schmiedekamp, Carl, Schmitz, Kai, Shapiro-Albert, Brent J., Siemens, Xavier, Simon, Joseph, Siwek, Magdalena S., Fiscella, Sophia V. Sosa, Stairs, Ingrid H., Stinebring, Daniel R., Stovall, Kevin, Susobhanan, Abhimanyu, Swiggum, Joseph K., Taylor, Stephen R., Turner, Jacob E., Unal, Caner, Vallisneri, Michele, Vecchio, Alberto, Vigeland, Sarah J., Wahl, Haley M., Witt, Caitlin A., Wright, David, Young, Olivia
Evidence has emerged for a stochastic signal correlated among 67 pulsars within the 15-year pulsar-timing data set compiled by the NANOGrav collaboration. Similar signals have been found in data from the European, Indian, Parkes, and Chinese PTAs. Th
Externí odkaz:
http://arxiv.org/abs/2411.14846
Autor:
Agazie, Gabriella, Baier, Jeremy G., Baker, Paul T., Becsy, Bence, Blecha, Laura, Boddy, Kimberly K., Brazier, Adam, Brook, Paul R., Burke-Spolaor, Sarah, Burnette, Rand, Casey-Clyde, J. Andrew, Charisi, Maria, Chatterjee, Shami, Cohen, Tyler, Cordes, James M., Cornish, Neil J., Crawford, Fronefield, Cromartie, H. Thankful, DeCesar, Megan E., Demorest, Paul B., Deng, Heling, Dey, Lankeswar, Dolch, Timothy, Ferrara, Elizabeth C., Fiore, William, Fonseca, Emmanuel, Freedman, Gabriel E., Gardiner, Emiko C., Gersbach, Kyle A., Glaser, Joseph, Good, Deborah C., Gultekin, Kayhan, Hazboun, Jeffrey S., Jennings, Ross J., Johnson, Aaron D., Kaplan, David L., Kelley, Luke Zoltan, Key, Joey S., Laal, Nima, Lam, Michael T., Lamb, William G., Larsen, Bjorn, Lazio, T. Joseph W., Lewandowska, Natalia, Liu, Tingting, Luo, Jing, Lynch, Ryan S., Ma, Chung-Pei, Madison, Dustin R., McEwen, Alexander, McKee, James W., McLaughlin, Maura A., Meyers, Patrick M., Mingarelli, Chiara M. F., Mitridate, Andrea, Nay, Jonathan, Nice, David J., Ocker, Stella Koch, Olum, Ken D., Pennucci, Timothy T., Petrov, Polina, Pol, Nihan S., Radovan, Henri A., Ransom, Scott M., Ray, Paul S., Runnoe, Jessie C., Saffer, Alexander, Sardesai, Shashwat C., Schmitz, Kai, Siemens, Xavier, Simon, Joseph, Siwek, Magdalena S., Smith, Tristan L., Fiscella, Sophia V. Sosa, Stairs, Ingrid H., Stinebring, Daniel R., Susobhanan, Abhimanyu, Swiggum, Joseph K., Taylor, Jacob, Taylor, Stephen R., Turner, Jacob E., Unal, Caner, Vallisneri, Michele, van Haasteren, Rutger, Verbiest, Joris, Vigeland, Sarah J., Witt, Caitlin A., Wright, David, Young, Olivia
Pulsar timing array observations have found evidence for an isotropic gravitational wave background with the Hellings-Downs angular correlations, expected from general relativity. This interpretation hinges on the measured shape of the angular correl
Externí odkaz:
http://arxiv.org/abs/2411.13472
Recent advances in foundational Vision Language Models (VLMs) have reshaped the evaluation paradigm in computer vision tasks. These foundational models, especially CLIP, have accelerated research in open-vocabulary computer vision tasks, including Op
Externí odkaz:
http://arxiv.org/abs/2411.12044
Autor:
Chen, Yifan, Daniel, Matthias, D'Orazio, Daniel J., Mitridate, Andrea, Sagunski, Laura, Xue, Xiao, Agazie, Gabriella, Baier, Jeremy G., Baker, Paul T., Bécsy, Bence, Blecha, Laura, Brazier, Adam, Brook, Paul R., Burke-Spolaor, Sarah, Burnette, Rand, Casey-Clyde, J. Andrew, Charisi, Maria, Chatterjee, Shami, Cohen, Tyler, Cordes, James M., Cornish, Neil J., Crawford, Fronefield, Cromartie, H. Thankful, DeCesar, Megan E., Demorest, Paul B., Deng, Heling, Dey, Lankeswar, Dolch, Timothy, Ferrara, Elizabeth C., Fiore, William, Fonseca, Emmanuel, Freedman, Gabriel E., Gardiner, Emiko C., Gersbach, Kyle A., Glaser, Joseph, Good, Deborah C., Gültekin, Kayhan, Hazboun, Jeffrey S., Jennings, Ross J., Johnson, Aaron D., Kaplan, David L., Kelley, Luke Zoltan, Key, Joey S., Laal, Nima, Lam, Michael T., Lamb, William G., Larsen, Bjorn, Lazio, T. Joseph W., Lewandowska, Natalia, Liu, Tingting, Luo, Jing, Lynch, Ryan S., Ma, Chung-Pei, Madison, Dustin R., McEwen, Alexander, McKee, James W., McLaughlin, Maura A., Meyers, Patrick M., Mingarelli, Chiara M. F., Nice, David J., Ocker, Stella Koch, Olum, Ken D., Pennucci, Timothy T., Petrov, Polina, Pol, Nihan S., Radovan, Henri A., Ransom, Scott M., Ray, Paul S., Romano, Joseph D., Runnoe, Jessie C., Saffer, Alexander, Sardesai, Shashwat C., Schmitz, Kai, Siemens, Xavier, Simon, Joseph, Siwek, Magdalena S., Fiscella, Sophia V. Sosa, Stairs, Ingrid H., Stinebring, Daniel R., Susobhanan, Abhimanyu, Swiggum, Joseph K., Taylor, Jacob, Taylor, Stephen R., Turner, Jacob E., Unal, Caner, Vallisneri, Michele, van Haasteren, Rutger, Verbiest, Joris, Vigeland, Sarah J., Witt, Caitlin A., Wright, David, Young, Olivia
The detection of a stochastic gravitational wave background by pulsar timing arrays suggests the presence of a supermassive black hole binary population. Although the observed spectrum generally aligns with predictions from orbital evolution driven b
Externí odkaz:
http://arxiv.org/abs/2411.05906
3D visual grounding consists of identifying the instance in a 3D scene which is referred by an accompanying language description. While several architectures have been proposed within the commonly employed grounding-by-selection framework, the utiliz
Externí odkaz:
http://arxiv.org/abs/2411.03405
Disentangled representation learning aims to represent the underlying generative factors of a dataset in a latent representation independently of one another. In our work, we propose a discrete variational autoencoder (VAE) based model where the grou
Externí odkaz:
http://arxiv.org/abs/2409.14851
Autor:
Gencali, Ali Arda, Ertan, Unal
We have investigated the evolutionary connections of the isolated neutron star (NS) populations including radio pulsars (RPs), anomalous X-ray pulsars (AXPs), soft gamma repeaters (SGRs), dim isolated NSs (XDINs), ``high-magnetic-field'' RPs (``HBRPs
Externí odkaz:
http://arxiv.org/abs/2409.11595
3D segmentation is a core problem in computer vision and, similarly to many other dense prediction tasks, it requires large amounts of annotated data for adequate training. However, densely labeling 3D point clouds to employ fully-supervised training
Externí odkaz:
http://arxiv.org/abs/2409.08102
In this work, we introduce Scribbles for All, a label and training data generation algorithm for semantic segmentation trained on scribble labels. Training or fine-tuning semantic segmentation models with weak supervision has become an important topi
Externí odkaz:
http://arxiv.org/abs/2408.12489