Nipun Kwatra
Nipun Kwatra
Computer Science, Stanford University
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Texture optimization for example-based synthesis
V Kwatra, I Essa, A Bobick, N Kwatra
ACM SIGGRAPH 2005 Papers, 795-802, 2005
Two-way coupled SPH and particle level set fluid simulation
F Losasso, J Talton, N Kwatra, R Fedkiw
IEEE Transactions on Visualization and Computer Graphics 14 (4), 797-804, 2008
Gandiva: Introspective cluster scheduling for deep learning
W Xiao, R Bhardwaj, R Ramjee, M Sivathanu, N Kwatra, Z Han, P Patel, ...
13th {USENIX} Symposium on Operating Systems Design and Implementation …, 2018
A method for avoiding the acoustic time step restriction in compressible flow
N Kwatra, J Su, JT Grétarsson, R Fedkiw
Journal of Computational Physics 228 (11), 4146-4161, 2009
Texturing fluids
V Kwatra, D Adalsteinsson, T Kim, N Kwatra, M Carlson, M Lin
IEEE transactions on visualization and computer graphics 13 (5), 939-952, 2007
A framework for activity recognition and detection of unusual activities
D Mahajan, N Kwatra, S Jain, P Kalra, S Banerjee
Indian Conference on Computer Vision, Graphics and Image Processing, 2004
Numerically stable fluid–structure interactions between compressible flow and solid structures
JT Grétarsson, N Kwatra, R Fedkiw
Journal of Computational Physics 230 (8), 3062-3084, 2011
Fluid simulation with articulated bodies
N Kwatra, C Wojtan, M Carlson, IA Essa, PJ Mucha, G Turk
IEEE Transactions on Visualization and Computer Graphics 16 (1), 70-80, 2009
Practical Animation of Compressible Flow for ShockWaves and Related Phenomena.
N Kwatra, J Gretarsson, R Fedkiw
Symposium on Computer Animation, 207-215, 2010
Asynchronous evolution for fully‐implicit and semi‐implicit time integration
C Schroeder, N Kwatra, W Zheng, R Fedkiw
Computer Graphics Forum 30 (7), 1983-1992, 2011
Balancing efficiency and fairness in heterogeneous GPU clusters for deep learning
S Chaudhary, R Ramjee, M Sivathanu, N Kwatra, S Viswanatha
Proceedings of the Fifteenth European Conference on Computer Systems, 1-16, 2020
Unsupervised clustering using pseudo-semi-supervised learning
D Gupta, R Ramjee, N Kwatra, M Sivathanu
International Conference on Learning Representations, 2019
Dynamic binary space partitioning for hidden surface removal
A Kumar, V Kwatra, B Singh, S Kapoor, A Kumar, V Kwatra, B Singh, ...
Indian Conference on Computer Vision, Graphics and Image Processing 27, 487-496, 2005
An Introduction to Planar Curve Compression
B Whitley, H McEwan, N Kwatra
Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule
N Iyer, V Thejas, N Kwatra, R Ramjee, M Sivathanu
arXiv preprint arXiv:2003.03977, 2020
AutoLR: A Method for Automatic Tuning of Learning Rate
N Kwatra, V Thejas, N Iyer, R Ramjee, M Sivathanu
Practical Methods for Simulation of Compressible Flow and Structure Interactions
N Kwatra
Stanford University, 2011
A Computational Study on the Internal Splash Effect
L Cooper, C Wojtan, N Kwatra, P Mucha
APS Division of Fluid Dynamics Meeting Abstracts 61, MR. 004, 2008
Classifying Ground Pixels for Robotics Applications
D Kim, N Kwatra, D Maturana
sensors 4 (6), 7-9, 2006
Augmented Reality
N Kwatra, S Jain
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Artiklar 1–20