Publications
My Google Scholar 📝 profile.
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A Scalable Approach to Covariate and Concept Drift Management via Adaptive Data Segmentation Vennela Yarabolu, Govind Waghmare, Sonia Gupta, Siddhartha Asthana International Conference on Data Science and Management of Data (CODS-COMAD), 2024 |
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Learning Temporal Representations of Bipartite Financial Graphs Pritam Kumar Nath, Govind Waghmare, Nikhil Tumbde, Nitish Kumar, Siddhartha Asthana International Conference on AI in Finance (ICAIF), 2023 |
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TBoost: Gradient Boosting Temporal Graph Neural Networks Pritam Nath, Govind Waghmare, Nancy Agrawal, Nitish Kumar, Siddhartha Asthana Temporal Graph Learning Workshop @ NeurIPS, 2023 |
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Modeling Inter-Dependence Between Time and Mark in Multivariate Temporal Point Processes Govind Waghmare, Ankur Debnath, Siddhartha Asthana, Aakarsh Malhotra Conference on Information & Knowledge Management (CIKM), 2022 |
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Adversarial Generation of Temporal Data: A Critique on Fidelity of Synthetic Data Ankur Debnath, Nitish Gupta, Govind Waghmare, Hardik Wadhwa, Siddhartha Asthana, Ankur Arora Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2021 |
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Exploring generative data augmentation in multivariate time series forecasting: opportunities and challenges Ankur Debnath, Govind Waghmare, Hardik Wadhwa, Siddhartha Asthana, Ankur Arora KDD Workshop on Mining and Learning from Time Series (MileTS), 2021 |
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Unsupervised cross-modal alignment for multi-person 3d pose estimation Jogendra Nath Kundu, Ambareesh Revanur, Govind Waghmare, Rahul Mysore Venkatesh, R Venkatesh Babu European Conference on Computer Vision (ECCV), 2020 |
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Badminton shuttlecock detection and prediction of trajectory using multiple 2 dimensional scanners Govind Waghmare, Sneha Borkar, Vishal Saley, Hemant Chinchore, Shivraj Wabale IEEE First International Conference on Control, Measurement and Instrumentation (CMI), 2016 |