| Multi-sensor prognostics using an unsupervised health index based on LSTM encoder-decoder P Malhotra, V Tv, A Ramakrishnan, G Anand, L Vig, P Agarwal, G Shroff arXiv preprint arXiv:1608.06154, 2016 | 287 | 2016 |
| TimeNet: Pre-trained deep recurrent neural network for time series classification P Malhotra, V TV, L Vig, P Agarwal, G Shroff arXiv preprint arXiv:1706.08838, 2017 | 251 | 2017 |
| 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 arXiv preprint arXiv:1709.01073, 2017 | 204 | 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 Proceedings of the acm india joint international conference on data science …, 2018 | 120 | 2018 |
| Meta-Learning for Black-box Optimization V TV, P Malhotra, J Narwariya, V Lovekesh, S Gautam European Conference on Machine Learning and Principles and Practice of …, 2019 | 74* | 2019 |
| Meta-learning for few-shot time series classification J Narwariya, P Malhotra, L Vig, G Shroff, TV Vishnu Proceedings of the 7th ACM IKDD CoDS and 25th COMAD, 28-36, 2020 | 60 | 2020 |
| Graph neural networks for leveraging industrial equipment structure: An application to remaining useful life estimation J Narwariya, P Malhotra, V TV, L Vig, G Shroff arXiv preprint arXiv:2006.16556, 2020 | 31 | 2020 |
| Recurrent neural networks for online remaining useful life estimation in ion mill etching system T Vishnu, P Gupta, P Malhotra, L Vig, G Shroff Proceedings of the annual conference of the phm society, philadelphia, pa …, 2018 | 23 | 2018 |
| Multi-sensor prognostics using an unsupervised health index based on LSTM encoder-decoder. arXiv 2016 P Malhotra, V Tv, A Ramakrishnan, G Anand, L Vig, P Agarwal, G Shroff arXiv preprint arXiv:1608.06154, 0 | 19 | |
| 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 | 16 | 2017 |
| Multi-sensor prognostics using an unsupervised health index based on LSTM encoder-decoder. arXiv P Malhotra, V Tv, A Ramakrishnan, G Anand, L Vig, P Agarwal, G Shroff arXiv preprint arXiv:1608.06154, 2016 | 14 | 2016 |
| Data-driven prognostics with predictive uncertainty estimation using ensemble of deep ordinal regression models TV Vishnu, D Chavan, P Malhotra, L Vig, G Shroff International Journal of Prognostics and Health Management 10 (4), 2019 | 12 | 2019 |
| 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 | |
| Data-driven prognostics with predictive uncertainty estimation using ensemble of deep ordinal regression models V TV, P Malhotra, L Vig, G Shroff arXiv preprint arXiv:1903.09795, 2019 | 11 | 2019 |
| On practical aspects of using RNNs for fault detection in sparsely-labeled multi-sensor time series N Gugulothu, TV Vishnu, P Gupta, P Malhotra, L Vig, P Agarwal, G Shroff Annual Conference of the PHM Society 10 (1), 2018 | 10 | 2018 |
| TimeNet: Pre-trained deep recurrent neural network for time series classification. arXiv 2017 P Malhotra, V Tv, L Vig, P Agarwal, G Shroff arXiv preprint arXiv:1706.08838, 0 | 8 | |
| TimeNet: Pre-trained deep recurrent neural network for time series classification. arXiv P Malhotra, V Tv, L Vig, P Agarwal, G Shroff arXiv preprint arXiv:1706.08838, 2017 | 7 | 2017 |
| Regularizing fully convolutional networks for time series classification by decorrelating filters K Paneri, TV Vishnu, P Malhotra, L Vig, G Shroff Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 10003 …, 2019 | 6 | 2019 |
| Bayesian networks for interpretable health monitoring of complex systems TV Vishnu, N Gugulothu, P Malhotra, L Vig, P Agarwal, G Shroff Workshop on AI for Internet of Things at IJCAI, 2017 | 6 | 2017 |
| 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 | 5 | 2020 |
Pankaj MalhotraMicrosoftVerified email at microsoft.com
