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Vipin Kumar 0001
Person information
- affiliation: University of Minnesota, Department of Computer Science and Engineering, USA
Other persons with the same name
- Vipin Kumar — disambiguation page
- Vipin Kumar 0002 — Jawaharlal Nehru University, School of Computer and Systems Sciences, New Delhi, India
- Vipin Kumar 0003 — Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany (and 1 more)
- Vipin Kumar 0004 — Lovely Professional University, Department of Computer Science Engineering, India
- Vipin Kumar 0005 — Bharat Electronics Limited, Product Development & Innovation Center, Bangalore, India
- Vipin Kumar 0006 — University of Maryland College Park, Laboratory for Pattern Analysis, Computer Science Departmen, MD, USA
- Vipin Kumar 0007 — National Institute of Technology Sikkim, Department of Electronics and Communication Engineering, Ravangla, India
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2020 – today
- 2024
- [c234]Shaoming Xu, Ankush Khandelwal, Arvind Renganathan, Vipin Kumar:
Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling. SDM 2024: 307-315 - [c233]Rahul Ghosh, Arvind Renganathan, Wallace McAliley, Michael S. Steinbach, Christopher J. Duffy, Vipin Kumar:
Towards Entity-Aware Conditional Variational Inference for Heterogeneous Time-Series Prediction: An application to Hydrology. SDM 2024: 334-342 - [c232]Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal, Xiaowei Jia, David J. Mulla, Vipin Kumar:
Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach. SDM 2024: 445-453 - [c231]Somya Sharma Chatterjee, Kelly Lindsay, Neel Chatterjee, Rohan Patil, Ilkay Altintas De Callafon, Michael S. Steinbach, Daniel Giron, Mai H. Nguyen, Vipin Kumar:
Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management. SDM 2024: 589-597 - [i49]Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal, Xiaowei Jia, David J. Mulla, Vipin Kumar:
Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach. CoRR abs/2401.15875 (2024) - [i48]Anuj Karpatne, Xiaowei Jia, Vipin Kumar:
Knowledge-guided Machine Learning: Current Trends and Future Prospects. CoRR abs/2403.15989 (2024) - [i47]Praveen Ravirathinam, Ankush Khandelwal, Rahul Ghosh, Vipin Kumar:
Towards a Knowledge guided Multimodal Foundation Model for Spatio-Temporal Remote Sensing Applications. CoRR abs/2407.19660 (2024) - [i46]Rahul Ghosh, Zac McEachran, Arvind Renganathan, Kelly Lindsay, Somya Sharma Chatterjee, Michael S. Steinbach, John Nieber, Christopher J. Duffy, Vipin Kumar:
Hierarchically Disentangled Recurrent Network for Factorizing System Dynamics of Multi-scale Systems. CoRR abs/2407.20152 (2024) - 2023
- [j97]Jared Willard, Xiaowei Jia, Shaoming Xu, Michael S. Steinbach, Vipin Kumar:
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems. ACM Comput. Surv. 55(4): 66:1-66:37 (2023) - [j96]Chenxi Lin, Zhenong Jin, David J. Mulla, Rahul Ghosh, Kaiyu Guan, Vipin Kumar, Yaping Cai:
Correction: Lin et al. Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens. 2021, 13, 1740. Remote. Sens. 15(1): 141 (2023) - [c230]Vipin Kumar:
Knowledge-Guided Machine Learning: A New Framework for Accelerating Scientific Discovery and Addressing Global Environmental Challenges. IEEE Big Data 2023: 2 - [c229]Kshitij Tayal, Arvind Renganathan, Rahul Ghosh, Xiaowei Jia, Vipin Kumar:
Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling. ICDM 2023: 588-597 - [c228]Xindong Wu, Xingquan Zhu, Elena Baralis, Ruqian Lu, Vipin Kumar, Leszek Rutkowski, Jie Tang:
On Computing Paradigms - Where Will Large Language Models Be Going. ICDM 2023: 1577-1582 - [c227]Haoyu Yang, Roshan Tourani, Jia Li, Pedro J. Caraballo, Michael S. Steinbach, Vipin Kumar, György J. Simon:
Causal Structure Learning from Imperfect Longitudinal Data in Healthcare. ICHI 2023: 1-11 - [c226]Praveen Ravirathinam, Rahul Ghosh, Ke Wang, Keyang Xuan, Ankush Khandelwal, Hilary Dugan, Paul C. Hanson, Vipin Kumar:
Spatiotemporal Classification with limited labels using Constrained Clustering for large datasets. SDM 2023: 487-495 - [c225]Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar:
Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications. SDM 2023: 649-657 - [c224]Somya Sharma, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher J. Duffy, Vipin Kumar:
Probabilistic Inverse Modeling: An Application in Hydrology. SDM 2023: 847-855 - [i45]Leikun Yin, Rahul Ghosh, Chenxi Lin, David Hale, Christoph Weigl, James Obarowski, Junxiong Zhou, Jessica Till, Xiaowei Jia, Troy Mao, Vipin Kumar, Zhenong Jin:
Mapping smallholder cashew plantations to inform sustainable tree crop expansion in Benin. CoRR abs/2301.00363 (2023) - [i44]Rahul Ghosh, Haoyu Yang, Ankush Khandelwal, Erhu He, Arvind Renganathan, Somya Sharma, Xiaowei Jia, Vipin Kumar:
Entity Aware Modelling: A Survey. CoRR abs/2302.08406 (2023) - [i43]Longbing Cao, Hui Chen, Xuhui Fan, João Gama, Yew-Soon Ong, Vipin Kumar:
Bayesian Federated Learning: A Survey. CoRR abs/2304.13267 (2023) - [i42]Hector Zenil, Jesper Tegnér, Felipe S. Abrahão, Alexander Lavin, Vipin Kumar, Jeremy G. Frey, Adrian Weller, Larisa N. Soldatova, Alan R. Bundy, Nicholas R. Jennings, Koichi Takahashi, Lawrence Hunter, Saso Dzeroski, Andrew Briggs, Frederick D. Gregory, Carla P. Gomes, Christopher K. I. Williams, Jon Rowe, James A. Evans, Hiroaki Kitano, Joshua B. Tenenbaum, Ross D. King:
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence. CoRR abs/2307.07522 (2023) - [i41]Jared D. Willard, Charuleka Varadharajan, Xiaowei Jia, Vipin Kumar:
Time Series Predictions in Unmonitored Sites: A Survey of Machine Learning Techniques in Water Resources. CoRR abs/2308.09766 (2023) - [i40]Kshitij Tayal, Arvind Renganathan, Rahul Ghosh, Xiaowei Jia, Vipin Kumar:
Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling. CoRR abs/2309.10291 (2023) - [i39]Shaoming Xu, Ankush Khandelwal, Arvind Renganathan, Vipin Kumar:
Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling. CoRR abs/2309.16882 (2023) - [i38]Somya Sharma Chatterjee, Kelly Lindsay, Neel Chatterjee, Rohan Patil, Ilkay Altintas De Callafon, Michael S. Steinbach, Daniel Giron, Mai H. Nguyen, Vipin Kumar:
Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management. CoRR abs/2310.01593 (2023) - [i37]Somya Sharma Chatterjee, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher J. Duffy, Vipin Kumar:
Uncertainty Quantification in Inverse Models in Hydrology. CoRR abs/2310.02193 (2023) - [i36]Arvind Renganathan, Rahul Ghosh, Ankush Khandelwal, Vipin Kumar:
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Heterogeneous Systems. CoRR abs/2310.04727 (2023) - 2022
- [c223]Rahul Ghosh, Xiaowei Jia, Leikun Yin, Chenxi Lin, Zhenong Jin, Vipin Kumar:
Clustering augmented self-supervised learning: an application to land cover mapping. SIGSPATIAL/GIS 2022: 3:1-3:10 - [c222]Rahul Ghosh, Bangyan Li, Kshitij Tayal, Vipin Kumar, Xiaowei Jia:
Meta-Transfer Learning: An application to Streamflow modeling in River-streams. ICDM 2022: 161-170 - [c221]Rahul Ghosh, Arvind Renganathan, Kshitij Tayal, Xiang Li, Ankush Khandelwal, Xiaowei Jia, Christopher J. Duffy, John Nieber, Vipin Kumar:
Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology. KDD 2022: 465-474 - [c220]Kshitij Tayal, Xiaowei Jia, Rahul Ghosh, Jared Willard, Jordan S. Read, Vipin Kumar:
Invertibility aware Integration of Static and Time-series data: An application to Lake Temperature Modeling. SDM 2022: 702-710 - [i35]Somya Sharma, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher J. Duffy, Vipin Kumar:
Probabilistic Inverse Modeling: An Application in Hydrology. CoRR abs/2210.06213 (2022) - [i34]Praveen Ravirathinam, Rahul Ghosh, Ke Wang, Keyang Xuan, Ankush Khandelwal, Hilary Dugan, Paul C. Hanson, Vipin Kumar:
Spatiotemporal Classification with limited labels using Constrained Clustering for large datasets. CoRR abs/2210.07522 (2022) - [i33]Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar:
Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications. CoRR abs/2210.08347 (2022) - [i32]Jia Li, Xiang Li, Xiaowei Jia, Michael S. Steinbach, Vipin Kumar:
Realization of Causal Representation Learning to Adjust Confounding Bias in Latent Space. CoRR abs/2211.08573 (2022) - 2021
- [j95]Haoyu Yang, Roshan Tourani, Ying Zhu, Vipin Kumar, Genevieve B. Melton, Michael S. Steinbach, György J. Simon:
Strategies for building robust prediction models using data unavailable at prediction time. J. Am. Medical Informatics Assoc. 29(1): 72-79 (2021) - [j94]Chenxi Lin, Zhenong Jin, David J. Mulla, Rahul Ghosh, Kaiyu Guan, Vipin Kumar, Yaping Cai:
Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote. Sens. 13(9): 1740 (2021) - [j93]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar:
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles. Trans. Data Sci. 2(3): 20:1-20:26 (2021) - [j92]Yolanda Gil, Daniel Garijo, Deborah Khider, Craig A. Knoblock, Varun Ratnakar, Maximiliano Osorio, Hernán Vargas, Minh Pham, Jay Pujara, Basel Shbita, Binh Vu, Yao-Yi Chiang, Dan Feldman, Yijun Lin, Hayley Song, Vipin Kumar, Ankush Khandelwal, Michael S. Steinbach, Kshitij Tayal, Shaoming Xu, Suzanne A. Pierce, Lissa Pearson, Daniel Hardesty-Lewis, Ewa Deelman, Rafael Ferreira da Silva, Rajiv Mayani, Armen R. Kemanian, Yuning Shi, Lorne Leonard, Scott D. Peckham, Maria Stoica, Kelly M. Cobourn, Zeya Zhang, Christopher J. Duffy, Lele Shu:
Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making. ACM Trans. Interact. Intell. Syst. 11(2): 11:1-11:49 (2021) - [j91]Wonsuk Oh, Michael S. Steinbach, M. Regina Castro, Kevin A. Peterson, Vipin Kumar, Pedro J. Caraballo, György J. Simon:
A Computational Method for Learning Disease Trajectories From Partially Observable EHR Data. IEEE J. Biomed. Health Informatics 25(7): 2476-2486 (2021) - [c219]Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar:
Attention-augmented Spatio-Temporal Segmentation for Land Cover Mapping. IEEE BigData 2021: 1399-1408 - [c218]Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Ankush Khandelwal, David J. Mulla, Vipin Kumar:
CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels. IEEE BigData 2021: 1625-1632 - [c217]Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Steven Markstrom, Jared Willard, Shaoming Xu, Michael S. Steinbach, Jordan S. Read, Vipin Kumar:
Physics-Guided Recurrent Graph Model for Predicting Flow and Temperature in River Networks. SDM 2021: 612-620 - [i31]Rahul Ghosh, Xiaowei Jia, Vipin Kumar:
Land Cover Mapping in Limited Labels Scenario: A Survey. CoRR abs/2103.02429 (2021) - [i30]Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar:
Attention-augmented Spatio-Temporal Segmentation for Land Cover Mapping. CoRR abs/2105.02963 (2021) - [i29]Kshitij Tayal, Raunak Manekar, Zhong Zhuang, David Yang, Vipin Kumar, Felix Hofmann, Ju Sun:
Phase Retrieval using Single-Instance Deep Generative Prior. CoRR abs/2106.04812 (2021) - [i28]Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Ankush Khandelwal, David J. Mulla, Vipin Kumar:
CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels. CoRR abs/2107.12499 (2021) - [i27]Rahul Ghosh, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar:
Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping. CoRR abs/2108.07323 (2021) - [i26]Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Vipin Kumar:
Weakly Supervised Classification Using Group-Level Labels. CoRR abs/2108.07330 (2021) - [i25]Rahul Ghosh, Arvind Renganathan, Ankush Khandelwal, Xiaowei Jia, Xiang Li, John Nieber, Christopher J. Duffy, Vipin Kumar:
Knowledge-guided Self-supervised Learning for estimating River-Basin Characteristics. CoRR abs/2109.06429 (2021) - 2020
- [j90]György J. Simon, Kevin A. Peterson, M. Regina Castro, Michael S. Steinbach, Vipin Kumar, Pedro J. Caraballo:
Predicting diabetes clinical outcomes using longitudinal risk factor trajectories. BMC Medical Informatics Decis. Mak. 20(1): 6 (2020) - [j89]Xiaowei Jia, Ankush Khandelwal, Kimberly Carlson, James Gerber, Paul C. West, Leah H. Samberg, Vipin Kumar:
Automated Plantation Mapping in Southeast Asia Using MODIS Data and Imperfect Visual Annotations. Remote. Sens. 12(4): 636 (2020) - [j88]Saurabh Agrawal, Michael S. Steinbach, Daniel Boley, Snigdhansu Chatterjee, Gowtham Atluri, Anh The Dang, Stefan Liess, Vipin Kumar:
Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks. IEEE Trans. Knowl. Data Eng. 32(9): 1798-1811 (2020) - [c216]Kshitij Tayal, Rahul Ghosh, Vipin Kumar:
Model-agnostic Methods for Text Classification with Inherent Noise. COLING (Industry) 2020: 202-213 - [c215]Kshitij Tayal, Nikhil Rao, Saurabh Agarwal, Xiaowei Jia, Karthik Subbian, Vipin Kumar:
Regularized Graph Convolutional Networks for Short Text Classification. COLING (Industry) 2020: 236-242 - [c214]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar:
Process Guided Deep Learning for Modeling Physical Systems: An Application in Lake Temperature Modeling. IGARSS 2020: 3494-3496 - [c213]Xiaowei Jia, Handong Zhao, Zhe Lin, Ajinkya Kale, Vipin Kumar:
Personalized Image Retrieval with Sparse Graph Representation Learning. KDD 2020: 2735-2743 - [c212]Huaxiu Yao, Xiaowei Jia, Vipin Kumar, Zhenhui Li:
Learning with Small Data. KDD 2020: 3539-3540 - [c211]Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Varun Mithal, Vipin Kumar:
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data. SDM 2020: 253-261 - [i24]Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Varun Mithal, Vipin Kumar:
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data. CoRR abs/2001.00994 (2020) - [i23]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar:
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles. CoRR abs/2001.11086 (2020) - [i22]Jared Willard, Xiaowei Jia, Shaoming Xu, Michael S. Steinbach, Vipin Kumar:
Integrating Physics-Based Modeling with Machine Learning: A Survey. CoRR abs/2003.04919 (2020) - [i21]Kshitij Tayal, Chieh-Hsin Lai, Vipin Kumar, Ju Sun:
Inverse Problems, Deep Learning, and Symmetry Breaking. CoRR abs/2003.09077 (2020) - [i20]Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Steven Markstrom, Jared Willard, Shaoming Xu, Michael S. Steinbach, Jordan S. Read, Vipin Kumar:
Physics-Guided Recurrent Graph Networks for Predicting Flow and Temperature in River Networks. CoRR abs/2009.12575 (2020) - [i19]Jared D. Willard, Jordan S. Read, Alison P. Appling, Samantha K. Oliver, Xiaowei Jia, Vipin Kumar:
Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning. CoRR abs/2011.05369 (2020) - [i18]Jia Li, Xiaowei Jia, Haoyu Yang, Vipin Kumar, Michael S. Steinbach, György J. Simon:
Teaching deep learning causal effects improves predictive performance. CoRR abs/2011.05466 (2020) - [i17]Ankush Khandelwal, Shaoming Xu, Xiang Li, Xiaowei Jia, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar:
Physics Guided Machine Learning Methods for Hydrology. CoRR abs/2012.02854 (2020)
2010 – 2019
- 2019
- [b3]Pang-Ning Tan, Michael S. Steinbach, Anuj Karpatne, Vipin Kumar:
Introduction to Data Mining (Second Edition). Pearson 2019 - [j87]Yolanda Gil, Suzanne A. Pierce, Hassan A. Babaie, Arindam Banerjee, Kirk D. Borne, Gary S. Bust, Michelle Cheatham, Imme Ebert-Uphoff, Carla P. Gomes, Mary C. Hill, John D. Horel, Leslie Hsu, Jim Kinter, Craig A. Knoblock, David M. Krum, Vipin Kumar, Pierre F. J. Lermusiaux, Yan Liu, Chris North, Victor Pankratius, Shanan Peters, Beth Plale, Allen Pope, Sai Ravela, Juan Restrepo, Aaron J. Ridley, Hanan Samet, Shashi Shekhar:
Intelligent systems for geosciences: an essential research agenda. Commun. ACM 62(1): 76-84 (2019) - [j86]Xiaowei Jia, Ankush Khandelwal, Kimberly Carlson, James Gerber, Paul C. West, Vipin Kumar:
Plantation Mapping in Southeast Asia. Frontiers Big Data 2: 46 (2019) - [j85]Anuj Karpatne, Imme Ebert-Uphoff, Sai Ravela, Hassan Ali Babaie, Vipin Kumar:
Machine Learning for the Geosciences: Challenges and Opportunities. IEEE Trans. Knowl. Data Eng. 31(8): 1544-1554 (2019) - [c210]Pranjul Yadav, Michael S. Steinbach, M. Regina Castro, Pedro J. Caraballo, Vipin Kumar, György J. Simon:
Frequent Causal Pattern Mining: A Computationally Efficient Framework For Estimating Bias-Corrected Effects. IEEE BigData 2019: 1981-1990 - [c209]Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Varun Mithal, Vipin Kumar:
Spatio-temporal classification at multiple resolutions using multi-view regularization. IEEE BigData 2019: 4117-4120 - [c208]Xiaowei Jia, Mengdie Wang, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring. IJCAI 2019: 2628-2634 - [c207]Daniel Garijo, Deborah Khider, Varun Ratnakar, Yolanda Gil, Ewa Deelman, Rafael Ferreira da Silva, Craig A. Knoblock, Yao-Yi Chiang, Minh Pham, Jay Pujara, Binh Vu, Dan Feldman, Rajiv Mayani, Kelly M. Cobourn, Christopher J. Duffy, Armen R. Kemanian, Lele Shu, Vipin Kumar, Ankush Khandelwal, Kshitij Tayal, Scott D. Peckham, Maria Stoica, Anna Dabrowski, Daniel Hardesty-Lewis, Suzanne A. Pierce:
An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models. IUI Companion 2019: 111-112 - [c206]Xiaowei Jia, Sheng Li, Handong Zhao, Sungchul Kim, Vipin Kumar:
Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training? KDD 2019: 1665-1673 - [c205]Wonsuk Oh, Michael S. Steinbach, M. Regina Castro, Kevin A. Peterson, Vipin Kumar, Pedro J. Caraballo, György J. Simon:
Evaluating the Impact of Data Representation on EHR-Based Analytic Tasks. MedInfo 2019: 288-292 - [c204]Xiaowei Jia, Sheng Li, Ankush Khandelwal, Guruprasad Nayak, Anuj Karpatne, Vipin Kumar:
Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection. SDM 2019: 513-521 - [c203]Xiaowei Jia, Guruprasad Nayak, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
Classifying Heterogeneous Sequential Data by Cyclic Domain Adaptation: An Application in Land Cover Detection. SDM 2019: 540-548 - [c202]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob Zwart, Michael S. Steinbach, Vipin Kumar:
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles. SDM 2019: 558-566 - [e19]Ankur Teredesai, Vipin Kumar, Ying Li, Rómer Rosales, Evimaria Terzi, George Karypis:
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019. ACM 2019, ISBN 978-1-4503-6201-6 [contents] - [i16]Xiaowei Jia, Ankush Khandelwal, Vipin Kumar:
Automated Monitoring Cropland Using Remote Sensing Data: Challenges and Opportunities for Machine Learning. CoRR abs/1904.04329 (2019) - [i15]Saurabh Agrawal, Saurabh Verma, Anuj Karpatne, Stefan Liess, Snigdhansu Chatterjee, Vipin Kumar:
A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series. CoRR abs/1906.01450 (2019) - 2018
- [j84]Pranjul Yadav, Michael S. Steinbach, Vipin Kumar, György J. Simon:
Mining Electronic Health Records (EHRs): A Survey. ACM Comput. Surv. 50(6): 85:1-85:40 (2018) - [j83]Gowtham Atluri, Anuj Karpatne, Vipin Kumar:
Spatio-Temporal Data Mining: A Survey of Problems and Methods. ACM Comput. Surv. 51(4): 83:1-83:41 (2018) - [j82]Varun Mithal, Guruprasad Nayak, Ankush Khandelwal, Vipin Kumar, Ramakrishna R. Nemani, Nikunj C. Oza:
Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework. Remote. Sens. 10(1): 69 (2018) - [j81]Chengzhang Zhu, Longbing Cao, Qiang Liu, Jianping Yin, Vipin Kumar:
Heterogeneous Metric Learning of Categorical Data with Hierarchical Couplings. IEEE Trans. Knowl. Data Eng. 30(7): 1254-1267 (2018) - [c201]Jia Li, Mengdie Wang, Michael S. Steinbach, Vipin Kumar, György J. Simon:
Don't Do Imputation: Dealing with Informative Missing Values in EHR Data Analysis. ICBK 2018: 415-422 - [c200]Guruprasad Nayak, Varun Mithal, Xiaowei Jia, Vipin Kumar:
Classifying Multivariate Time Series by Learning Sequence-level Discriminative Patterns. SDM 2018: 252-260 - [i14]Saurabh Agrawal, Saurabh Verma, Gowtham Atluri, Anuj Karpatne, Stefan Liess, Angus W. MacDonald III, Snigdhansu Chatterjee, Vipin Kumar:
Mining Sub-Interval Relationships In Time Series Data. CoRR abs/1802.06095 (2018) - [i13]Xiaowei Jia, Anuj Karpatne, Jared Willard, Michael S. Steinbach, Jordan S. Read, Paul C. Hanson, Hilary A. Dugan, Vipin Kumar:
Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes. CoRR abs/1810.02880 (2018) - [i12]Saurabh Agrawal, Michael S. Steinbach, Daniel Boley, Snigdhansu Chatterjee, Gowtham Atluri, Anh The Dang, Stefan Liess, Vipin Kumar:
Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks. CoRR abs/1810.02950 (2018) - [i11]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob Zwart, Michael S. Steinbach, Vipin Kumar:
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles. CoRR abs/1810.13075 (2018) - 2017
- [j80]Steven G. Johnson, Stuart M. Speedie, György J. Simon, Vipin Kumar, Bonnie L. Westra:
Quantifying the Effect of Data Quality on the Validity of an eMeasure. Appl. Clin. Inform. 08(04): 1012-1021 (2017) - [j79]Anuj Karpatne, Gowtham Atluri, James H. Faghmous, Michael S. Steinbach, Arindam Banerjee, Auroop R. Ganguly, Shashi Shekhar, Nagiza F. Samatova, Vipin Kumar:
Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data. IEEE Trans. Knowl. Data Eng. 29(10): 2318-2331 (2017) - [j78]Varun Mithal, Guruprasad Nayak, Ankush Khandelwal, Vipin Kumar, Nikunj C. Oza, Ramakrishna R. Nemani:
RAPT: Rare Class Prediction in Absence of True Labels. IEEE Trans. Knowl. Data Eng. 29(11): 2484-2497 (2017) - [c199]Xiaowei Jia, Yifan Hu, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
Joint sparse auto-encoder: A semi-supervised spatio-temporal approach in mapping large-scale croplands. IEEE BigData 2017: 1173-1182 - [c198]Wonsuk Oh, Pranjul Yadav, Vipin Kumar, Pedro J. Caraballo, M. Regina Castro, Michael S. Steinbach, György J. Simon:
Estimating Disease Onset Time by Modeling Lab Result Trajectories via Bayes Networks. ICHI 2017: 374-379 - [c197]Anuj Karpatne, Vipin Kumar:
Big Data in Climate: Opportunities and Challenges for Machine Learning. KDD 2017: 21-22 - [c196]Saurabh Agrawal, Gowtham Atluri, Anuj Karpatne, William Haltom, Stefan Liess, Snigdhansu Chatterjee, Vipin Kumar:
Tripoles: A New Class of Relationships in Time Series Data. KDD 2017: 697-706 - [c195]Xiaowei Jia, Ankush Khandelwal, Guruprasad Nayak, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar:
Incremental Dual-memory LSTM in Land Cover Prediction. KDD 2017: 867-876 - [c194]Xiaowei Jia, Ankush Khandelwal, Guruprasad Nayak, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar:
Predict Land Covers with Transition Modeling and Incremental Learning. SDM 2017: 171-179 - [r5]Varun Chandola, Arindam Banerjee, Vipin Kumar:
Active Learning. Encyclopedia of Machine Learning and Data Mining 2017: 42-56 - [i10]Pranjul Yadav, Michael S. Steinbach, Vipin Kumar, György J. Simon:
Mining Electronic Health Records: A Survey. CoRR abs/1702.03222 (2017) - [i9]Anuj Karpatne, William Watkins, Jordan S. Read, Vipin Kumar:
Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling. CoRR abs/1710.11431 (2017) - [i8]Anuj Karpatne, Imme Ebert-Uphoff, Sai Ravela, Hassan Ali Babaie, Vipin Kumar:
Machine Learning for the Geosciences: Challenges and Opportunities. CoRR abs/1711.04708 (2017) - [i7]Gowtham Atluri, Anuj Karpatne, Vipin Kumar:
Spatio-Temporal Data Mining: A Survey of Problems and Methods. CoRR abs/1711.04710 (2017) - [i6]Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
ORBIT: Ordering Based Information Transfer Across Space and Time for Global Surface Water Monitoring. CoRR abs/1711.05799 (2017) - [i5]Xiaowei Jia, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
Discovery of Shifting Patterns in Sequence Classification. CoRR abs/1712.07203 (2017) - 2016
- [j77]Stuart M. Speedie, György J. Simon, Vipin Kumar, Bonnie L. Westra, Steven G. Johnson:
Application of an Ontology for Characterizing Data Quality for a Secondary Use of EHR Data. Appl. Clin. Inform. 07(01): 69-88 (2016) - [j76]