Zobrazeno 1 - 10
of 464
pro vyhledávání: '"Pandey Shivam"'
Autor:
Sui, Ce, Bartlett, Deaglan J., Pandey, Shivam, Desmond, Harry, Ferreira, Pedro G., Wandelt, Benjamin D.
Current and future large scale structure surveys aim to constrain the neutrino mass and the equation of state of dark energy. We aim to construct accurate and interpretable symbolic approximations to the linear and nonlinear matter power spectra as a
Externí odkaz:
http://arxiv.org/abs/2410.14623
We develop a transformer-based conditional generative model for discrete point objects and their properties. We use it to build a model for populating cosmological simulations with gravitationally collapsed structures called dark matter halos. Specif
Externí odkaz:
http://arxiv.org/abs/2409.11401
Autor:
Pandey, Shivam, Modi, Chirag, Wandelt, Benjamin D., Bartlett, Deaglan J., Bayer, Adrian E., Bryan, Greg L., Ho, Matthew, Lavaux, Guilhem, Makinen, T. Lucas, Villaescusa-Navarro, Francisco
To maximize the amount of information extracted from cosmological datasets, simulations that accurately represent these observations are necessary. However, traditional simulations that evolve particles under gravity by estimating particle-particle i
Externí odkaz:
http://arxiv.org/abs/2409.09124
Many modern applications of Bayesian inference, such as in cosmology, are based on complicated forward models with high-dimensional parameter spaces. This considerably limits the sampling of posterior distributions conditioned on observed data. In tu
Externí odkaz:
http://arxiv.org/abs/2409.09101
Semi-analytic methods can generate baryon-corrected fields from N-body simulations (``baryonification'') and are rapidly becoming a ubiquitous tool in modeling structure formation on non-linear scales. We extend this formalism to consistently model t
Externí odkaz:
http://arxiv.org/abs/2409.03822
Autor:
Ganapati Raju N.V., Nyalakanti Nikhil, Kambampati Premsai, Kanthali Yeshwanth, Pandey Shivam, Maithili K.
Publikováno v:
E3S Web of Conferences, Vol 430, p 01081 (2023)
Clickbait is a significant problem on online media platforms. It misleads users and manipulates their engagement. A user who clicks on a clickbait link may be taken to a website full of ads, or that requires them to pay for something. The goal of thi
Externí odkaz:
https://doaj.org/article/e8a97d739f6a4bd49fc299e287da4159
Autor:
Demirbozan, Umut, Nadathur, Seshadri, Ferrero, Ismael, Fosalba, Pablo, Kovacs, Andras, Miquel, Ramon, Davies, Christopher T., Pandey, Shivam, Adamow, Monika, Bechtol, Keith, Drlica-Wagner, Alex, Gruendl, Robert, Hartley, Will, Pieres, Adriano, Ross, Ashley, Rykoff, Eli, Sheldon, Erin, Yanny, Brian, Abbott, Tim, Aguena, Michel, Allam, Sahar, Alves, Otavio, Bacon, David, Bertin, Emmanuel, Bocquet, Sebastian, Brooks, David, Rosell, Aurelio Carnero, Carretero, Jorge, Cawthon, Ross, da Costa, Luiz, Pereira, Maria Elidaiana da Silva, De Vicente, Juan, Desai, Shantanu, Doel, Peter, Everett, Spencer, Flaugher, Brenna, Friedel, Douglas, Frieman, Josh, Gatti, Marco, Gaztanaga, Enrique, Giannini, Giulia, Gutierrez, Gaston, Hinton, Samuel, Hollowood, Devon L., James, David, Jeffrey, Niall, Kuehn, Kyler, Lahav, Ofer, Lee, Sujeong, Marshall, Jennifer, Mena-Fernández, Juan, Mohr, Joe, Myles, Justin, Ogando, Ricardo, Malagón, Andrés Plazas, Roodman, Aaron, Sanchez, Eusebio, Sevilla, Ignacio, Smith, Mathew, Soares-Santos, Marcelle, Suchyta, Eric, Swanson, Molly, Tarle, Gregory, Weaverdyck, Noah, Weller, Jochen, Wiseman, Philip
$ $Low density cosmic voids gravitationally lens the cosmic microwave background (CMB), leaving a negative imprint on the CMB convergence $\kappa$. This effect provides insight into the distribution of matter within voids, and can also be used to stu
Externí odkaz:
http://arxiv.org/abs/2404.18278
This paper describes our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness. The challenge is focused on automatically detecting the degree of relatedness between pairs of sentences for 14 languages including both high and low
Externí odkaz:
http://arxiv.org/abs/2404.04513
Autor:
Lee, Max E., Genel, Shy, Wandelt, Benjamin D., Zhang, Benjamin, Delgado, Ana Maria, Pandey, Shivam, Lau, Erwin T., Carr, Christopher, Cook, Harrison, Nagai, Daisuke, Angles-Alcazar, Daniel, Villaescusa-Navarro, Francisco, Bryan, Greg L.
Galaxy formation models within cosmological hydrodynamical simulations contain numerous parameters with non-trivial influences over the resulting properties of simulated cosmic structures and galaxy populations. It is computationally challenging to s
Externí odkaz:
http://arxiv.org/abs/2403.10609
Autor:
Ho, Matthew, Bartlett, Deaglan J., Chartier, Nicolas, Cuesta-Lazaro, Carolina, Ding, Simon, Lapel, Axel, Lemos, Pablo, Lovell, Christopher C., Makinen, T. Lucas, Modi, Chirag, Pandya, Viraj, Pandey, Shivam, Perez, Lucia A., Wandelt, Benjamin, Bryan, Greg L.
Publikováno v:
2024 OJA, Vol. 7
This paper presents the Learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline, a codebase for rapid, user-friendly, and cutting-edge machine learning (ML) inference in astrophysics and cosmology. The pipeline includes software for im
Externí odkaz:
http://arxiv.org/abs/2402.05137