Kumar Sricharan
Water Science and Technology · 2010–2013
A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Water Science and Technology — 21 citations into it; #1,434 of 1,711 by trust here, #1,371 by citations
- Global and Planetary Change — 17 citations into it; #8,588 of 10,225 by trust here, #8,787 by citations
- Environmental Engineering — 11 citations into it; #4,856 of 5,479 by trust here, #4,524 by citations
- Statistics and Probability — 10 citations into it; #6,731 of 12,932 by trust here, #10,275 by citations
- Artificial Intelligence — 7 citations into it; #18,423 of 35,345 by trust here, #31,361 by citations
- Computer Vision and Pattern Recognition — 5 citations into it
- Signal Processing — 5 citations into it
Whom Kumar Sricharan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Nikolai N. Leonenko
- Paul A. Viola
- D. Loftsgaarden
- Eric Learned-Miller
- Qing Wang
- Anukool Lakhina
- Hoshin V. Gupta
- C. Quesenberry
- John W. Fisher III
- William M. Wells
Who trusts Kumar Sricharan overall
- Barnab'as P'oczos
- Jeff Schneider
- Akshay Krishnamurthy
- Liang Xiong
- Kirthevasan Kandasamy
- Chaopeng Shen
Papers from Kumar Sricharan's perspective
Ordered by how strongly the researchers Kumar Sricharan trusts endorse each paper. Same corpus, a different order for every researcher.
- The future of distributed models: model calibration and uncertainty prediction.
- A nonparametric estimate of a multivariate density function
- Maximum likelihood Bayesian averaging of uncertain model predictions
- Bayesian recursive parameter estimation for hydrologic models
- A class of Rényi information estimators for multidimensional densities
- Towards reduced uncertainty in conceptual rainfall‐runoff modelling: dynamic identifiability analysis
- Multilevel calibration strategy for complex hydrologic simulation models
- Independent Component Analysis
- Estimating the uncertain mathematical structure of a water balance model via Bayesian data assimilation
- Multi-model ensemble hydrologic prediction using Bayesian model averaging
Their papers
- Empirical estimation of entropy functionals with confidence (2010) — 46 citations
- Estimating epistemic and aleatory uncertainties during hydrologic modeling: An information theoretic approach (2013) — 122 citations