| Towards enabling trusted artificial intelligence via blockchain K Sarpatwar, R Vaculin, H Min, G Su, T Heath, G Ganapavarapu, ... Policy-based autonomic data governance, 137-153, 2019 | 59 | 2019 |
| AutoAI-TS: AutoAI for time series forecasting SY Shah, D Patel, L Vu, XH Dang, B Chen, P Kirchner, H Samulowitz, ... Proceedings of the 2021 International Conference on Management of Data, 2584 …, 2021 | 49 | 2021 |
| Blockchain enabled AI marketplace: the price you pay for trust K Sarpatwar, V Sitaramagiridharganesh Ganapavarapu, K Shanmugam, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 26 | 2019 |
| Dqa: Scalable, automated and interactive data quality advisor S Shrivastava, D Patel, A Bhamidipaty, WM Gifford, SA Siegel, ... 2019 IEEE International Conference on Big Data (Big Data), 2913-2922, 2019 | 20 | 2019 |
| Anomalykits: Anomaly detection toolkit for time series D Patel, G Ganapavarapu, S Jayaraman, S Lin, A Bhamidipaty, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 13209 …, 2022 | 16 | 2022 |
| Aggregated machine learning verification for database VS Ganapavarapu, K Sarpatwar, K Shanmugam, R Vaculin US Patent 11,694,110, 2023 | 15 | 2023 |
| Efficient verification of machine learning applications VS Ganapavarapu, K Sarpatwar, K Shanmugam, R Vaculin US Patent 11,983,608, 2024 | 9 | 2024 |
| Differentially private distributed data summarization under covariate shift K Sarpatwar, K Shanmugam, VS Ganapavarapu, A Jagmohan, R Vaculin Advances in Neural Information Processing Systems 32, 2019 | 7 | 2019 |
| TsSHAP: Robust model agnostic feature-based explainability for time series forecasting VC Raykar, A Jati, S Mukherjee, N Aggarwal, K Sarpatwar, ... arXiv preprint arXiv:2303.12316, 2023 | 6 | 2023 |
| Efficient verification of machine learning applications VS Ganapavarapu, K Sarpatwar, K Shanmugam, R Vaculin US Patent 11,562,228, 2023 | 6 | 2023 |
| Electronically verifying a process flow E Valdez, RH Boivie, VS Ganapavarapu, J Jung, GJ Nam, R Vaculin, ... US Patent 11,356,275, 2022 | 5 | 2022 |
| Efficient unsupervised anomaly detection on homomorphically encrypted data K Sarpatwar, VS Ganapavarapu, S Sathe, R Vaculin US Patent 11,271,958, 2022 | 3 | 2022 |
| AI Explainability 360 Toolkit for Time-Series and Industrial Use Cases G Ganapavarapu, S Mukherjee, N Martinez Gil, K Sarpatwar, ... Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 2 | 2023 |
| Verification of stochastic gradient descent K Sarpatwar, K Shanmugam, VS Ganapavarapu, R Vaculin US Patent 11,475,365, 2022 | 2 | 2022 |
| Scaling Anomaly Detection Service Using Serverless Technology D Patel, S Lin, S Jayaraman, G Ganapavarapu, A Bhamidipaty, ... 2021 IEEE International Conference on Big Data (Big Data), 5982-5984, 2021 | 1 | 2021 |
| Identifying Homogeneous and Interpretable Groups for Conformal Prediction NM Gil, D Patel, C Reddy, G Ganapavarapu, R Vaculin, J Kalagnanam Proceedings of the Fortieth Conference on Uncertainty in Artificial …, 2024 | | 2024 |
| Robust Feature Based Model Agnostic Explainability For Time Series Forecasting V Raykar, S Mukherjee, B Vinzamuri, G Ganapavarapu, N Aggarwal INFORMS Annual Meeting, 2021 | | 2021 |
| AutoAI-TS: AutoAI for Time Series Forecasting S Yousaf Shah, D Patel, L Vu, XH Dang, B Chen, P Kirchner, ... arXiv e-prints, arXiv: 2102.12347, 2021 | | 2021 |
| Identifying Homogeneous and Interpretable Groups for Conformal Prediction N Martinez, DC Patel, C Reddy, G Ganapavarapu, R Vaculin, ... The 40th Conference on Uncertainty in Artificial Intelligence, 0 | | |
