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of 155
pro vyhledávání: '"Balakrishnan, Kaushik"'
The task of 2D human pose estimation is challenging as the number of keypoints is typically large (~ 17) and this necessitates the use of robust neural network architectures and training pipelines that can capture the relevant features from the input
Externí odkaz:
http://arxiv.org/abs/2204.10209
Autor:
Balakrishnan, Kaushik, Bellan, Josette
Publikováno v:
In International Journal of Multiphase Flow September 2024 179
Autor:
Balakrishnan, Kaushik
High explosive charges when detonated ensue in a flow field characterized by several physical phenomena that include blast wave propagation, hydrodynamic instabilities, real gas effects, fluid mixing and afterburn effects. Solid metal particles are o
Externí odkaz:
http://hdl.handle.net/1853/34672
Dynamical systems are ubiquitous and are often modeled using a non-linear system of governing equations. Numerical solution procedures for many dynamical systems have existed for several decades, but can be slow due to high-dimensional state space of
Externí odkaz:
http://arxiv.org/abs/2109.05095
Autor:
Zubov, Kirill, McCarthy, Zoe, Ma, Yingbo, Calisto, Francesco, Pagliarino, Valerio, Azeglio, Simone, Bottero, Luca, Luján, Emmanuel, Sulzer, Valentin, Bharambe, Ashutosh, Vinchhi, Nand, Balakrishnan, Kaushik, Upadhyay, Devesh, Rackauckas, Chris
Physics-informed neural networks (PINNs) are an increasingly powerful way to solve partial differential equations, generate digital twins, and create neural surrogates of physical models. In this manuscript we detail the inner workings of NeuralPDE.j
Externí odkaz:
http://arxiv.org/abs/2107.09443
Training robots to navigate diverse environments is a challenging problem as it involves the confluence of several different perception tasks such as mapping and localization, followed by optimal path-planning and control. Recently released photo-rea
Externí odkaz:
http://arxiv.org/abs/2101.01774
Reaction-diffusion systems are ubiquitous in nature and in engineering applications, and are often modeled using a non-linear system of governing equations. While robust numerical methods exist to solve them, deep learning-based reduced ordermodels (
Externí odkaz:
http://arxiv.org/abs/2006.05547
Autor:
Balakrishnan, Kaushik
Publikováno v:
Available to subscribers only..
Thesis (Ph.D.)--Southern Illinois University Carbondale, 2008.
"Department of Chemistry and Biochemistry." Includes bibliographical references (p. 207-227). Also available online.
"Department of Chemistry and Biochemistry." Includes bibliographical references (p. 207-227). Also available online.
Autor:
Pan, Zhihong, Shenoy, Rahul, Balakrishnan, Kaushik, Cheng, Qisen, Lee, Janghwan, Jeon, Yongmoon, Jeong, Deokyeong, Kim, Jaewon
Publikováno v:
SID Symposium Digest of Technical Papers; Jun2024, Vol. 55 Issue 1, p409-412, 4p