Publications

My Google Scholar 📝 profile.



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
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
TBoost: Gradient Boosting Temporal Graph Neural Networks
Pritam Nath, Govind Waghmare, Nancy Agrawal, Nitish Kumar, Siddhartha Asthana
Temporal Graph Learning Workshop @ NeurIPS, 2023
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
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
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
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
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