Követés
Vishnu TV
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
2192016
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
1492017
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
1462017
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
632018
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
43*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
262020
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
192020
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
14
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
122018
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
92019
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
92017
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
82018
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
82016
Data-driven prognostics with predictive uncertainty estimation using ensemble of deep ordinal regression models
TV Vishnu, P Malhotra, L Vig, G Shroff
International Journal of Prognostics and Health Management 10 (4), 2019
72019
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
7
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
P Malhotra, V TV, L Vig, P Agarwal, G Shroff
arXiv preprint arXiv:1706.08838, 2017
52017
TimeNet: Pre-trained deep recurrent neural network for time series classification. arXiv 2017
P Malhotra, T Vishnu, L Vig, P Agarwal, GM Shroff
arXiv preprint arXiv:1706.08838, 0
5
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
32019
Failed and censored instances based remaining useful life (rul) estimation of entities
P Malhotra, V Tv, L Vig, G Shroff
US Patent App. 16/352,587, 2020
22020
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