| Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks N Gugulothu, V TV, P Malhotra, L Vig, P Agarwal, G Shroff INTERNATIONAL JOURNAL OF PROGNOSTICS AND HEALTH MANAGEMENT 9 (1), 13, 2018 | 198 | 2018 |
| Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks N Gugulothu, V TV, P Malhotra, L Vig, P Agarwal, G Shroff 2nd ACM SIGKDD Workshop on Machine Learning for Prognostics and Health …, 2017 | 198 | 2017 |
| Online Anomaly Detection with Concept Drift Adaptation using Recurrent Neural Networks S Saurav, P Malhotra, V TV, N Gugulothu, L Vig, P Agarwal, G Shroff CoDS-COMAD 2018, 2018 | 115 | 2018 |
| Sparse Neural Networks for Anomaly Detection in High-Dimensional Time Series N Gugulothu, P Malhotra, L Vig, G Shroff AI4IOT Workshop at IJCAI 2018, 2018 | 37 | 2018 |
| Predicting remaining useful life using time series embeddings based on recurrent neural networks (2017) N Gugulothu, V Tv, P Malhotra, L Vig, P Agarwal, G Shroff arXiv preprint arXiv:1709.01073, 2017 | 15 | 2017 |
| Predicting remaining useful life using time series embeddings based on recurrent neural networks. arXiv 2017 N Gugulothu, V Tv, P Malhotra, L Vig, P Agarwal, G Shroff arXiv preprint arXiv:1709.01073, 0 | 12 | |
| On Practical Aspects of Using RNNs for Fault Detection in Sparsely-Labeled Multi-sensor Time Series N Gugulothu, V TV, P Gupta, P Malhotra, L Vig, P Agarwal, G Shroff Annual Conference of the Prognostics and Health Management Society 10 (1), 2018 | 10 | 2018 |
| Time series prediction with confidence estimates using sparse recurrent mixture density networks N Gugulothu, EN Subramanian, SP Bhat US Patent 11,556,789, 2023 | 6 | 2023 |
| Bayesian Networks for Interpretable Health Monitoring of Complex Systems TV Vishnu, N Gugulothu, P Malhotra, L Vig, P Agarwal, G Shroff AI4IOT Workshop at Internationation Joint Conference on Artificial …, 2017 | 6 | 2017 |
| Load Forecasting in Energy Markets: An Approach Using Sparse Neural Networks N Gugulothu, E Subramanian Proceedings of the Tenth ACM International Conference on Future Energy …, 2019 | 4 | 2019 |
| Sparse Recurrent Mixture Density Networks for Forecasting High Variability Time Series with Confidence Estimates N Gugulothu, E Subramanian, SP Bhat International Conference on Artificial Neural Networks, 422-433, 2019 | 3 | 2019 |
| Sparse neural network based anomaly detection in multi-dimensional time series P Malhotra, N Gugulothu, L Vig, G Shroff US Patent 11,429,837, 2022 | 1 | 2022 |
| Methods and systems for obtaining end-to-end classification model using mixture density network N Gugulothu, SP Bhat, T Bodas US Patent App. 18/367,025, 2024 | | 2024 |
| Mixture Density Networks for Classification with an Application to Product Bundling N Gugulothu, SP Bhat, T Bodas arXiv preprint arXiv:2402.05428, 2024 | | 2024 |
| Method and system for health monitoring and fault signature identification P Malhotra, TV Vishnu, N Gugulothu, L Vig, P Agarwal, G Shroff US Patent 10,719,774, 2020 | | 2020 |
| Learning Algorithms for Dynamic Pricing: A Comparative Study C Amballa, N Gugulothu, MK Gupta, SP Bhat | | 2020 |
Pankaj MalhotraMicrosoftVerified email at microsoft.com
