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Santosh Kumar Srivastava
Santosh Kumar Srivastava
Staff Data Scientist Olea Edge Analytics Austin Texas
Verified email at oleaedge.com - Homepage
Title
Cited by
Cited by
Year
Comprehensive assessment of T-cell receptor β-chain diversity in αβ T cells
HS Robins, PV Campregher, SK Srivastava, A Wacher, CJ Turtle, ...
Blood, The Journal of the American Society of Hematology 114 (19), 4099-4107, 2009
13172009
Overlap and effective size of the human CD8+ T cell receptor repertoire
HS Robins, SK Srivastava, PV Campregher, CJ Turtle, J Andriesen, ...
Science translational medicine 2 (47), 47ra64-47ra64, 2010
5062010
Bayesian quadratic discriminant analysis.
S Srivastava, MR Gupta, BA Frigyik
Journal of Machine Learning Research 8 (6), 2007
3052007
Logical neural networks
R Riegel, A Gray, F Luus, N Khan, N Makondo, IY Akhalwaya, H Qian, ...
arXiv preprint arXiv:2006.13155, 2020
1652020
Functional Bregman divergence and Bayesian estimation of distributions
BA Frigyik, S Srivastava, MR Gupta
IEEE Transactions on Information Theory 54 (11), 5130-5139, 2008
152*2008
Completely lazy learning
EK Garcia, S Feldman, MR Gupta, S Srivastava
IEEE Transactions on Knowledge and Data Engineering 22 (9), 1274-1285, 2009
762009
An introduction to functional derivatives
BA Frigyik, S Srivastava, MR Gupta
Dept. Electr. Eng., Univ. Washington, Seattle, WA, Tech. Rep 1, 2008
582008
Quantum embedding of knowledge for reasoning
D Garg, S Ikbal, SK Srivastava, H Vishwakarma, H Karanam, ...
Advances in Neural Information Processing Systems 32, 2019
552019
Parametric Bayesian estimation of differential entropy and relative entropy
M Gupta, S Srivastava
Entropy 12 (4), 818-843, 2010
492010
Palindromic nucleotide analysis in human T cell receptor rearrangements
SK Srivastava, HS Robins
PLoS One 7 (12), e52250, 2012
262012
Abnormalities of the αβ T-cell receptor repertoire in advanced myelodysplastic syndrome
PV Campregher, SK Srivastava, HJ Deeg, HS Robins, EH Warren
Experimental hematology 38 (3), 202-212, 2010
232010
Distribution-based Bayesian minimum expected risk for discriminant analysis
S Srivastava, MR Gupta
2006 IEEE international symposium on information theory, 2294-2298, 2006
222006
Sygma: System for generalizable modular question answering overknowledge bases
S Neelam, U Sharma, H Karanam, S Ikbal, P Kapanipathi, I Abdelaziz, ...
arXiv preprint arXiv:2109.13430, 2021
162021
Bayesian estimation of the entropy of the multivariate Gaussian
S Srivastava, MR Gupta
2008 IEEE International Symposium on Information Theory, 1103-1107, 2008
162008
A benchmark for generalizable and interpretable temporal question answering over knowledge bases
S Neelam, U Sharma, H Karanam, S Ikbal, P Kapanipathi, I Abdelaziz, ...
arXiv preprint arXiv:2201.05793, 2022
122022
Logical neural networks (2020)
R Riegel, A Gray, F Luus, N Khan, N Makondo, IY Akhalwaya, H Qian, ...
arXiv preprint arXiv:2006.13155, 2006
122006
Inductive quantum embedding
SK Srivastava, D Khandelwal, D Madan, D Garg, H Karanam, ...
Advances in Neural Information Processing Systems 33, 16012-16024, 2020
72020
Logical neural networks, CoRR abs/2006.13155 (2020)
R Riegel, AG Gray, FPS Luus, N Khan, N Makondo, IY Akhalwaya, H Qian, ...
URL: https://arxiv. org/abs/2006 13155, 2020
62020
Fusing similarities and Euclidean features with generative classifiers
L Cazzanti, MR Gupta, S Srivastava
2009 12th International Conference on Information Fusion, 224-231, 2009
52009
Minimum expected risk estimation for near-neighbor classification
MR Gupta, S Srivastava, L Cazzanti
University of Washington Electrical Engineering Technical Report 2006 6, 2006
22006
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