Zobrazeno 1 - 10
of 289
pro vyhledávání: '"Nair Prasanth"'
Autor:
Course, Kevin, Nair, Prasanth B.
We consider the problem of inferring latent stochastic differential equations (SDEs) with a time and memory cost that scales independently with the amount of data, the total length of the time series, and the stiffness of the approximate differential
Externí odkaz:
http://arxiv.org/abs/2312.10550
Computational modeling of high entropy alloys (HEA) is challenging given the scalability issues of Density functional theory (DFT) and the non-availability of Interatomic potentials (IP) for molecular dynamics simulations (MD). This work presents a c
Externí odkaz:
http://arxiv.org/abs/2302.06844
Discipline-based education researchers produce knowledge that aims to help instructors improve student learning and educational outcomes. Yet, the information produced may not even reach the educators it is intended to influence. Prior work has found
Externí odkaz:
http://arxiv.org/abs/2209.07627
Autor:
Nair, Prasanth P, Narayanan, Vinod
Publikováno v:
In Aerospace Science and Technology December 2024 155 Part 3
Autor:
Paulose, Rini, Agrawal, Varsha, Arya, Rahul, Bijanu, Abhijit, Rajak, Gaurav, Nair, Prasanth K., Mishra, Deepti, Khan, Mohammed Akram, Bhisikar, Abhay, Singh, Upendra, Mondi, Paparao, Pendam, Jyoti, Srivastava, Avanish Kumar, Salammal, Shabi Thankaraj
Publikováno v:
In Construction and Building Materials 16 August 2024 439
Publikováno v:
Advances in Neural Information Processing Systems. Vol. 33 (2020), pp. 18716-18726
We present a method for learning generalized Hamiltonian decompositions of ordinary differential equations given a set of noisy time series measurements. Our method simultaneously learns a continuous time model and a scalar energy function for a gene
Externí odkaz:
http://arxiv.org/abs/2104.05096
Autor:
Evans, Trefor W., Nair, Prasanth B.
We introduce a stochastic variational inference procedure for training scalable Gaussian process (GP) models whose per-iteration complexity is independent of both the number of training points, $n$, and the number basis functions used in the kernel a
Externí odkaz:
http://arxiv.org/abs/2006.03015
Autor:
Nair Prasanth, Kandasamy Saveetha, Zhang Junzeng, Ji Xiuhong, Kirby Chris, Benkel Bernhard, Hodges Mark D, Critchley Alan T, Hiltz David, Prithiviraj Balakrishnan
Publikováno v:
BMC Genomics, Vol 13, Iss 1, p 643 (2012)
Abstract Background We have previously shown that lipophilic components (LPC) of the brown seaweed Ascophyllum nodosum (ANE) improved freezing tolerance in Arabidopsis thaliana. However, the mechanism(s) of this induced freezing stress tolerance is l
Externí odkaz:
https://doaj.org/article/56380df74885496d804deaa6ee0b0b7d
Publikováno v:
BioMedical Engineering OnLine, Vol 6, Iss 1, p 47 (2007)
Abstract Background: Arterial geometry variability is inevitable both within and across individuals. To ensure realistic prediction of cardiovascular flows, there is a need for efficient numerical methods that can systematically account for geometric
Externí odkaz:
https://doaj.org/article/0c1a0b6e9bea4758b3f1280cc7adec4e
Autor:
Srivastava, Rashika, Nair, Prasanth M., Dewry, Raju, Kulkarni, Nitish, Mani, Veena, Bhakat, Mukesh, Mondal, Goutam
Publikováno v:
In Journal of Trace Elements and Minerals September 2023 5