24 citations · 43 across the 12 of their papers we have counts for
17 papers
Understanding the complex dynamics of climate change in south-west Australia using Machine Learning
Alka Yadav, Sourish Das, K Shuvo Bakar +1
The Standardized Precipitation Index (SPI) is used to indicate the meteorological drought situation - a negative (or positive) value of SPI would imply a dry (or wet) condition in…
Prediction of COVID-19 Disease Progression in India : Under the Effect of National Lockdown
Sourish Das
In this policy paper, we implement the epidemiological SIR to estimate the basic reproduction number at national and state level. We also developed the statistical…
Causal Impact of Web Browsing and Other Factors on Research Publications
Bharathi Manjula . K, Sourish Das, Jehadeesan . R
In this paper, we study the causal impact of the web-search activity on the research publication. We considered observational prospective study design, where research activity of 2…
Understanding North Atlantic Climate Instabilities and Complex Interactions using Data Science
Alka Yadav, Sourish Das, Anirban Chakraborti +1
The North Atlantic Oscillation (NAO) index, a measure of sea-level atmospheric pressure variability, holds significant influence over weather patterns in North America and Northern…
A Bayesian Perspective of Statistical Machine Learning for Big Data
Rajiv Sambasivan, Sourish Das, Sujit K Sahu
Statistical Machine Learning (SML) refers to a body of algorithms and methods by which computers are allowed to discover important features of input data sets which are often very…
Modeling Nelson-Siegel Yield Curve using Bayesian Approach
Sourish Das
Yield curve modeling is an essential problem in finance. In this work, we explore the use of Bayesian statistical methods in conjunction with Nelson-Siegel model. We present the hi…
Modeling Risk and Return using Dirichlet Process Prior
Sourish Das, Aritra Halder, Ananya Lahiri +1
In this paper, we showed that the no-arbitrage condition holds if the market follows the mixture of the geometric Brownian motion (GBM). The mixture of GBM can incorporate heavy-ta…
Characterization of catastrophic instabilities: Market crashes as paradigm
Anirban Chakraborti, Kiran Sharma, Hirdesh K. Pharasi +3
Catastrophic events, though rare, do occur and when they occur, they have devastating effects. It is, therefore, of utmost importance to understand the complexity of the underlying…
Big Data Classification Using Augmented Decision Trees
Rajiv Sambasivan, Sourish Das
We present an algorithm for classification tasks on big data. Experiments conducted as part of this study indicate that the algorithm can be as accurate as ensemble methods such as…
Regularization and Variable Selection with Copula Prior
Rahul Sharma, Sourish Das
In this work, we show that under specific choices of the copula, the lasso, elastic net, and -prior are particular cases of `copula prior,' for regularization and variable selec…
Big Data Regression Using Tree Based Segmentation
Rajiv Sambasivan, Sourish Das
Scaling regression to large datasets is a common problem in many application areas. We propose a two step approach to scaling regression to large datasets. Using a regression tree…
Sparse Portfolio selection via Bayesian Multiple testing
Sourish Das, Rituparna Sen
We presented Bayesian portfolio selection strategy, via the factor asset pricing model. If the market is information efficient, the proposed strategy will mimic the market; oth…
A Statistical Machine Learning Approach to Yield Curve Forecasting
Rajiv Sambasivan, Sourish Das
Yield curve forecasting is an important problem in finance. In this work we explore the use of Gaussian Processes in conjunction with a dynamic modeling strategy, much like the Kal…
Understanding Sea Ice Melting via Functional Data Analysis
Purba Das, Ananya Lahiri, Sourish Das
In this article, we considered the problem of sea ice cover is melting. Considering the `satellite passive microwave remote sensing data' as functional data, we studied daily obser…
Clustering Mixed Datasets Using Homogeneity Analysis with Applications to Big Data
Rajiv Sambasivan, Sourish Das
Datasets with a mixture of numerical and categorical attributes are routinely encountered in many application domains. In this work we examine an approach to clustering such datase…
Fast Gaussian Process Regression for Big Data
Sourish Das, Sasanka Roy, Rajiv Sambasivan
Gaussian Processes are widely used for regression tasks. A known limitation in the application of Gaussian Processes to regression tasks is that the computation of the solution req…
Regularizing Portfolio Risk Analysis: A Bayesian Approach
Sourish Das, Aritra Halder, Dipak K. Dey
It is important for a portfolio manager to estimate and analyze recent portfolio volatility to keep the portfolio's risk within limit. Though the number of financial instruments in…