Zobrazeno 1 - 10
of 168
pro vyhledávání: '"Chatterjee, Snigdhansu"'
Autor:
Gharakhanyan, Vahe, Wirth, Luke J., Torres, Jose A. Garrido, Eisenberg, Ethan, Wang, Ting, Trinkle, Dallas R., Chatterjee, Snigdhansu, Urban, Alexander
The melting temperature is important for materials design because of its relationship with thermal stability, synthesis, and processing conditions. Current empirical and computational melting point estimation techniques are limited in scope, computat
Externí odkaz:
http://arxiv.org/abs/2403.03092
Autor:
Chatterjee, Somya Sharma, Ghosh, Rahul, Renganathan, Arvind, Li, Xiang, Chatterjee, Snigdhansu, Nieber, John, Duffy, Christopher, Kumar, Vipin
In hydrology, modeling streamflow remains a challenging task due to the limited availability of basin characteristics information such as soil geology and geomorphology. These characteristics may be noisy due to measurement errors or may be missing a
Externí odkaz:
http://arxiv.org/abs/2310.02193
Autor:
Sharma, Somya, Ghosh, Rahul, Renganathan, Arvind, Li, Xiang, Chatterjee, Snigdhansu, Nieber, John, Duffy, Christopher, Kumar, Vipin
The astounding success of these methods has made it imperative to obtain more explainable and trustworthy estimates from these models. In hydrology, basin characteristics can be noisy or missing, impacting streamflow prediction. For solving inverse p
Externí odkaz:
http://arxiv.org/abs/2210.06213
Bayesian hierarchical models are proposed for modeling tropical cyclone characteristics and their damage potential in the Atlantic basin. We model the joint probability distribution of tropical cyclone characteristics and their damage potential at tw
Externí odkaz:
http://arxiv.org/abs/2208.07899
Publikováno v:
Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14753-14773, 2022, https://proceedings.mlr.press/v162/majumdar22a.html
In the context of supervised parametric models, we introduce the concept of e-values. An e-value is a scalar quantity that represents the proximity of the sampling distribution of parameter estimates in a model trained on a subset of features to that
Externí odkaz:
http://arxiv.org/abs/2206.05391
Semiconductor device models are essential to understand the charge transport in thin film transistors (TFTs). Using these TFT models to draw inference involves estimating parameters used to fit to the experimental data. These experimental data can in
Externí odkaz:
http://arxiv.org/abs/2111.13296
High-dimensional data, where the dimension of the feature space is much larger than sample size, arise in a number of statistical applications. In this context, we construct the generalized multivariate sign transformation, defined as a vector divide
Externí odkaz:
http://arxiv.org/abs/2107.01103
Often the underlying system of differential equations driving a stochastic dynamical system is assumed to be known, with inference conditioned on this assumption. We present a Bayesian framework for discovering this system of differential equations u
Externí odkaz:
http://arxiv.org/abs/2101.04437
Autor:
Agrawal, Saurabh, Verma, Saurabh, Karpatne, Anuj, Liess, Stefan, Chatterjee, Snigdhansu, Kumar, Vipin
Traditional approaches focus on finding relationships between two entire time series, however, many interesting relationships exist in small sub-intervals of time and remain feeble during other sub-intervals. We define the notion of a sub-interval re
Externí odkaz:
http://arxiv.org/abs/1906.01450
Publikováno v:
Journal of Multivariate Analysis Volume 191, September 2022, 105013
Multivariate sign functions are often used for robust estimation and inference. We propose using data dependent weights in association with such functions. The proposed weighted sign functions retain desirable robustness properties, while significant
Externí odkaz:
http://arxiv.org/abs/1905.02700