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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
2572016
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
2112017
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
1872017
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
1002018
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
58*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
502020
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
272020
Recurrent neural networks for online remaining useful life estimation in ion mill etching system
TV Vishnu, P Gupta, P Malhotra, L Vig, G Shroff
Proceedings of the Annual Conference of the PHM Society, Philadelphia, PA …, 2018
182018
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
17
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
152017
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
132016
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
102019
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
10
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
92019
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
92018
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
62017
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
6
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
52019
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
52017
Deep ordinal regression for remaining useful life estimation from censored data
TV Vishnu, P Malhotra, L Vig, G Shroff
Joint Workshop on Deep Learning for Safety-Critical Applications in …, 2018
22018
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