Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Martinez, Carianne"'
Autor:
Potter, Kevin, Martinez, Carianne, Pradhan, Reina, Brozak, Samantha, Sleder, Steven, Wheeler, Lauren
Many climate processes are characterized using large systems of nonlinear differential equations; this, along with the immense amount of data required to parameterize complex interactions, means that Earth-System Model (ESM) simulations may take week
Externí odkaz:
http://arxiv.org/abs/2409.12815
Causal representation learning algorithms discover lower-dimensional representations of data that admit a decipherable interpretation of cause and effect; as achieving such interpretable representations is challenging, many causal learning algorithms
Externí odkaz:
http://arxiv.org/abs/2310.18471
We introduce physics-informed multimodal autoencoders (PIMA) - a variational inference framework for discovering shared information in multimodal scientific datasets representative of high-throughput testing. Individual modalities are embedded into a
Externí odkaz:
http://arxiv.org/abs/2202.03242
Autor:
Norris, Chance, Ayyaswamy, Abhinand, Vishnugopi, Bairav S., Martinez, Carianne, Roberts, Scott A., Mukherjee, Partha P.
Publikováno v:
In Energy Storage Materials March 2024 67
Autor:
Doughty, Hazel, Karessli, Nour, Leonard, Kathryn, Li, Boyi, Martinez, Carianne, Mobasher, Azadeh, Nagrani, Arsha, Yadav, Srishti
In this paper we present the details of Women in Computer Vision Workshop - WiCV 2020, organized in alongside virtual CVPR 2020. This event aims at encouraging the women researchers in the field of computer vision. It provides a voice to a minority (
Externí odkaz:
http://arxiv.org/abs/2101.03787
Autor:
Krygier, Michael C., LaBonte, Tyler, Martinez, Carianne, Norris, Chance, Sharma, Krish, Collins, Lincoln N., Mukherjee, Partha P., Roberts, Scott A.
Publikováno v:
Nature Communications 12, 5414 (2021)
Image-based simulation, the use of 3D images to calculate physical quantities, fundamentally relies on image segmentation to create the computational geometry. However, this process introduces image segmentation uncertainty because there is a variety
Externí odkaz:
http://arxiv.org/abs/2012.09913
Deep learning has been successfully applied to the segmentation of 3D Computed Tomography (CT) scans. Establishing the credibility of these segmentations requires uncertainty quantification (UQ) to identify untrustworthy predictions. Recent UQ archit
Externí odkaz:
http://arxiv.org/abs/1910.10793
Autor:
Martinez, Carianne1,2 (AUTHOR) cmarti5@sandia.gov, Bolintineanu, Dan S.1 (AUTHOR), Olson, Aaron1 (AUTHOR), Rodgers, Theron1 (AUTHOR), Donohoe, Brendan1 (AUTHOR), Potter, Kevin M.1 (AUTHOR), Roberts, Scott A.1 (AUTHOR), Pokharel, Reeju3 (AUTHOR), Forrest, Stephanie2 (AUTHOR), Moore, Nathan W.1 (AUTHOR)
Publikováno v:
Computational Mechanics. Sep2023, Vol. 72 Issue 3, p525-551. 27p.
Autor:
Johnson, Kyle L., Maestas, Demitri, Emery, John M., Grigoriu, Mircea D., Smith, Matthew D., Martinez, Carianne
Publikováno v:
In Computational Materials Science March 2022 204
Publikováno v:
Frontiers in Mechanical Engineering; 2024, p1-13, 13p