Zobrazeno 1 - 10
of 2 324
pro vyhledávání: '"Mukerji P"'
Autor:
Al-Fakih, Abdulrahman, Koeshidayatullah, A., Mukerji, Tapan, Al-Azani, Sadam, Kaka, SanLinn I.
Well log analysis is crucial for hydrocarbon exploration, providing detailed insights into subsurface geological formations. However, gaps and inaccuracies in well log data, often due to equipment limitations, operational challenges, and harsh subsur
Externí odkaz:
http://arxiv.org/abs/2412.00718
Although generative adversarial networks (GANs) have shown significant success in modeling data distributions for image datasets, their application to structured or tabular data, such as well logs, remains relatively underexplored. This study extends
Externí odkaz:
http://arxiv.org/abs/2411.19875
This paper explores whether and to what extent ambiguous communication can be beneficial to the sender in a persuasion problem, when the receiver (and possibly the sender) is ambiguity averse. We provide a concavification-like characterization of the
Externí odkaz:
http://arxiv.org/abs/2410.05504
Autor:
Mukerji, Abhimanyu, More, Sushant, Kannan, Ashwin Viswanathan, Ravi, Lakshmi, Chen, Hua, Kohli, Naman, Khawand, Chris, Mandalapu, Dinesh
With recent rapid growth in online shopping, AI-powered Engagement Surfaces (ES) have become ubiquitous across retail services. These engagement surfaces perform an increasing range of functions, including recommending new products for purchase, remi
Externí odkaz:
http://arxiv.org/abs/2408.11967
Autor:
Chung, Jaehong, Marcato, Agnese, Guiltinan, Eric J., Mukerji, Tapan, Viswanathan, Hari, Lin, Yen Ting, Santos, Javier E.
This study introduces a hybrid fluid simulation approach that integrates generative diffusion models with physics-based simulations, aiming at reducing the computational costs of flow simulations while still honoring all the physical properties of in
Externí odkaz:
http://arxiv.org/abs/2406.19333
Autor:
Kashefi, Ali, Mukerji, Tapan
Fourier neural operators (FNOs) are invariant with respect to the size of input images, and thus images with any size can be fed into FNO-based frameworks without any modification of network architectures, in contrast to traditional convolutional neu
Externí odkaz:
http://arxiv.org/abs/2402.11568
Autor:
Chung, Jaehong, Marcato, Agnese, Guiltinan, Eric J., Mukerji, Tapan, Lin, Yen Ting, Santos, Javier E.
Pore-scale simulations accurately describe transport properties of fluids in the subsurface. These simulations enhance our understanding of applications such as assessing hydrogen storage efficiency and forecasting CO$_2$ sequestration processes in u
Externí odkaz:
http://arxiv.org/abs/2312.04375
This study presents a Graph Neural Networks (GNNs)-based approach for predicting the effective elastic moduli of rocks from their digital CT-scan images. We use the Mapper algorithm to transform 3D digital rock images into graph datasets, encapsulati
Externí odkaz:
http://arxiv.org/abs/2310.19274
Autor:
Neesha Hussain-Shamsy, Amika Shah, Lori Wasserman, Greer Slyfield Cook, Kaeli Macdonald, Keisha Greene, Geetha Mukerji, Simone N. Vigod, Juveria Zaheer, Emily Seto
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Background Group psychotherapy, an effective treatment for common postpartum mental disorders (e.g. depression, anxiety), has increasingly been delivered virtually since the pandemic. This study aims to understand experiential aspects of par
Externí odkaz:
https://doaj.org/article/e31743be63b942d8ad5125ef046dd2db
Autor:
Janet A. Parsons, Jannah Wigle, Ian Zenlea, Noah Ivers, Geetha Mukerji, Alanna Landry, Zubin Punthakee, Cheril L. Clarson, Rayzel Shulman
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background The transition from pediatric to adult care is a vulnerable time for young people living with type 1 diabetes (T1D). Bridging the Gap (BTG) is an audit-and-feedback (AF) intervention aimed at improving both transitions-in-care pro
Externí odkaz:
https://doaj.org/article/21bdf417a4b54d47b4a99b51d0cdaefb