Detection of climate zones using multifractal detrended cross-correlation analysis: A spatio-temporal data mining approach. - Monidipa Das; Soumya K. Ghosh 001 (ICAPR, 2015)

Modeling Spatio-temporal Change Pattern using Mathematical Morphology. - Monidipa Das; Soumya K. Ghosh 001 (CODS, 2016)

Prediction of meteorological parameters: an a-posteriori probabilistic semantic kriging approach. - Shrutilipi Bhattacharjee; Monidipa Das; Soumya K. Ghosh 001; Shashi Shekhar 001 (SIGSPATIAL/GIS, 2016)

A cost-efficient approach for measuring Moran's index of spatial autocorrelation in geostationary satellite data. - Monidipa Das; Soumya K. Ghosh 001 (IGARSS, 2016)

Deep-STEP: A Deep Learning Approach for Spatiotemporal Prediction of Remote Sensing Data. - Monidipa Das; Soumya K. Ghosh 001 (IEEE Geosci. Remote. Sens. Lett., 2016)

Spatio-temporal Autocorrelation Analysis for Regional Land-cover Change Detection from Remote Sensing Data. - Monidipa Das; Soumya K. Ghosh 001 (CODS, 2017)

BESTED: An Exponentially Smoothed Spatial Bayesian Analysis Model for Spatio-temporal Prediction of Daily Precipitation. - Monidipa Das; Soumya K. Ghosh 001 (SIGSPATIAL/GIS, 2017)

Spatio-temporal Prediction under Scarcity of Influencing Variables: A Hybrid Probabilistic Graph-based Approach. - Monidipa Das; Soumya K. Ghosh 001 (ICAPR, 2017)

Spatio-Temporal Prediction of Meteorological Time Series Data: An Approach Based on Spatial Bayesian Network (SpaBN). - Monidipa Das; Soumya K. Ghosh 001 (PReMI, 2017)

semBnet: A semantic Bayesian network for multivariate prediction of meteorological time series data. - Monidipa Das; Soumya K. Ghosh 001 (Pattern Recognit. Lett., 2017)

Measuring Moran's I in a Cost-Efficient Manner to Describe a Land-Cover Change Pattern in Large-Scale Remote Sensing Imagery. - Monidipa Das; Soumya K. Ghosh 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017)

A Deep-Learning-Based Forecasting Ensemble to Predict Missing Data for Remote Sensing Analysis. - Monidipa Das; Soumya K. Ghosh 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017)

FORWARD: A Model for FOrecasting Reservoir WAteR Dynamics Using Spatial Bayesian Network (SpaBN). - Monidipa Das; Soumya K. Ghosh 001; Pramesh Gupta; V. M. Chowdary; Ravoori Nagaraja; Vinay K. Dadhwal (IEEE Trans. Knowl. Data Eng., 2017)

FORWARD: A Model for FOrecasting Reservoir WAteR Dynamics Using Spatial Bayesian Network (SpaBN) (Extended Abstract). - Monidipa Das; Soumya K. Ghosh 001; Pramesh Gupta; Vemuri M. Chowdary; Ravoori Nagaraja; Vinay Kumar Dadhwal (ICDE, 2018)

Data-driven approaches for meteorological time series prediction: A comparative study of the state-of-the-art computational intelligence techniques. - Monidipa Das; Soumya K. Ghosh 001 (Pattern Recognit. Lett., 2018)

Space-time Prediction of High Resolution Raster Data: An Approach based on Spatio-temporal Bayesian Network (STBN). - Monidipa Das; Soumya K. Ghosh 001 (COMAD/CODS, 2019)

Short-Term Load Forecasting: An Intelligent Approach Based on Recurrent Neural Network. - Atul Patel; Monidipa Das; Soumya K. Ghosh 001 (HIS, 2019)

MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream Classification. - Monidipa Das; Mahardhika Pratama; Septiviana Savitri; Jie Zhang 002 (ICDM, 2019)

FERNN: A Fast and Evolving Recurrent Neural Network Model for Streaming Data Classification. - Monidipa Das; Mahardhika Pratama; Andri Ashfahani; Subhrajit Samanta (IJCNN, 2019)

FB-STEP: A fuzzy Bayesian network based data-driven framework for spatio-temporal prediction of climatological time series data. - Monidipa Das; Soumya K. Ghosh 001 (Expert Syst. Appl., 2019)

A Skip-Connected Evolving Recurrent Neural Network for Data Stream Classification under Label Latency Scenario. - Monidipa Das; Mahardhika Pratama; Jie Zhang 002; Yew-Soon Ong (AAAI, 2020)

Online Prediction of Derived Remote Sensing Image Time Series: An Autonomous Machine Learning Approach. - Monidipa Das (IGARSS, 2020)

A Self-Evolving Mutually-Operative Recurrent Network-based Model for Online Tool Condition Monitoring in Delay Scenario. - Monidipa Das; Mahardhika Pratama; Tegoeh Tjahjowidodo (KDD, 2020)

Data-Driven Approaches for Spatio-Temporal Analysis: A Survey of the State-of-the-Arts. - Monidipa Das; Soumya K. Ghosh 001 (J. Comput. Sci. Technol., 2020)

SARDINE: A Self-Adaptive Recurrent Deep Incremental Network Model for Spatio-Temporal Prediction of Remote Sensing Data. - Monidipa Das; Mahardhika Pratama; Soumya K. Ghosh 001 (ACM Trans. Spatial Algorithms Syst., 2020)

Enhanced Bayesian Network Models for Spatial Time Series Prediction - Recent Research Trend in Data-Driven Predictive Analytics - Monidipa Das; Soumya K. Ghosh 001 (Springer, 2020)

Analyzing Impact of Climate Variability on COVID-19 Outbreak: A Semantically-enhanced Theory-guided Data-driven Approach. - Monidipa Das; Soumya K. Ghosh 001 (COMAD/CODS, 2021)

CateReR: A Graph Neural Network-Based Model for Category-Wise Reliability-Aware Recommendation. - Sucheta Dawn; Monidipa Das; Sanghamitra Bandyopadhyay (PReMI, 2021)

PReLim: A Modeling Paradigm for Remote Sensing Image Scene Classification Under Limited Labeled Samples. - Suparna Dutta; Monidipa Das (PReMI, 2021)

SELFIE: A Semantically-Enhanced Load Forecasting Approach with Indirect Estimate of Spatial Influences. - Monidipa Das; Suparna Dutta (TENCON, 2021)

Analyzing impact of parental occupation on child's learning performance: a semantics-driven probabilistic approach. - Monidipa Das (Int. J. Data Sci. Anal., 2021)

Real-time prediction of spatial raster time series: a context-aware autonomous learning model. - Monidipa Das (J. Real Time Image Process., 2021)

Does Climate Variability Impact COVID-19 Outbreak? An Enhanced Semantics-Driven Theory-Guided Model. - Monidipa Das; Akash Ghosh; Soumya K. Ghosh 001 (SN Comput. Sci., 2021)

Reducing Parameter Value Uncertainty in Discrete Bayesian Network Learning: A Semantic Fuzzy Bayesian Approach. - Monidipa Das; Soumya K. Ghosh 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2021)

A Model-Centric Explainer for Graph Neural Network based Node Classification. - Sayan Saha; Monidipa Das; Sanghamitra Bandyopadhyay (CIKM, 2022)

GraMMy: Graph representation learning based on micro-macro analysis. - Sucheta Dawn; Monidipa Das; Sanghamitra Bandyopadhyay (Neurocomputing, 2022)

Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements. - Monidipa Das; Soumya K. Ghosh 001; Vemuri M. Chowdary; Pabitra Mitra; Santosh Rijal (Remote. Sens., 2022)

A Multilayered Adaptive Recurrent Incremental Network Model for Heterogeneity-Aware Prediction of Derived Remote Sensing Image Time Series. - Monidipa Das; Soumya K. Ghosh 001; Sanghamitra Bandyopadhyay (IEEE Trans. Geosci. Remote. Sens., 2022)

GraphEx: A User-Centric Model-Level Explainer for Graph Neural Networks. - Sayan Saha; Monidipa Das; Sanghamitra Bandyopadhyay (Tiny Papers @ ICLR, 2023)

Remote sensing scene classification under scarcity of labelled samples - A survey of the state-of-the-arts. - Suparna Dutta; Monidipa Das (Comput. Geosci., 2023)

SoURA: a user-reliability-aware social recommendation system based on graph neural network. - Sucheta Dawn; Monidipa Das; Sanghamitra Bandyopadhyay (Neural Comput. Appl., 2023)

An autonomous lightweight model for aerial scene classification under labeled sample scarcity. - Suparna Dutta; Monidipa Das (Appl. Intell., 2023)

GrapHiSM: a graph-based hierarchical semantics-driven model for aerial scene classification under scarcity of labelled samples. - Monidipa Das; Suparna Dutta (Appl. Intell., 2023)

A Guided Input Sampling-Based Perturbative Approach for Explainable AI in Image-Based Application. - Arju Bano; Monidipa Das (ICPR (4), 2024)

Toward Causality-Based Explanation of Aerial Scene Classifiers. - Suparna Dutta; Monidipa Das; Ujjwal Maulik (IEEE Geosci. Remote. Sens. Lett., 2024)

Spatial-SMOTE for handling imbalance in spatial regression tasks. - Rahul Dasharath Gavas; Monidipa Das; Soumya K. Ghosh 001; Arpan Pal 001 (Multim. Tools Appl., 2024)

Lightweight deep learning models for aerial scene classification: A comprehensive survey. - Suparna Dutta; Monidipa Das; Ujjwal Maulik (Eng. Appl. Artif. Intell., 2025)

Enhancing model explainability through S-GuISE: A spectral clustering-guided input sampling scheme for explanation. - Arju Bano; Monidipa Das (Neurocomputing, 2025)