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ORCIDChandana Priya Nivarthi
Person information
- affiliation: University of Kassel, Intelligent Embedded Systems Lab, Germany
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Journal Articles
- 2023
[j1]Chandana Priya Nivarthi
, Stephan Vogt, Bernhard Sick:
Multi-Task Representation Learning for Renewable-Power Forecasting: A Comparative Analysis of Unified Autoencoder Variants and Task-Embedding Dimensions. Mach. Learn. Knowl. Extr. 5(3): 1214-1233 (2023)
Conference and Workshop Papers
- 2024
- [c6]Zhixin Huang, Yujiang He, Chandana Priya Nivarthi, Bernhard Sick, Christian Gruhl:
Time-Series Representation Learning via Heterogeneous Spatial-Temporal Contrasting for Remaining Useful Life Prediction. ICPR (27) 2024: 1-21 - [c5]Zhixin Huang, Yujiang He, Chandana Priya Nivarthi, Christian Gruhl, Bernhard Sick:
Spatial-Temporal Attention Graph Neural Network with Uncertainty Estimation for Remaining Useful Life Prediction. IJCNN 2024: 1-9 - [c4]Chandana Priya Nivarthi, Zhixin Huang, Christian Gruhl, Bernhard Sick:
Multi-Task Representation Learning with Temporal Attention for Zero-Shot Time Series Anomaly Detection. IJCNN 2024: 1-10 - 2023
- [c3]Chandana Priya Nivarthi, Bernhard Sick:
Towards Few-Shot Time Series Anomaly Detection with Temporal Attention and Dynamic Thresholding. ICMLA 2023: 1444-1450 - 2022
- [c2]Chandana Priya Nivarthi, Stephan Vogt, Bernhard Sick:
Unified Autoencoder with Task Embeddings for Multi-Task Learning in Renewable Power Forecasting. ICMLA 2022: 1530-1536 - 2021
- [c1]Christian Gruhl, Abdul Hannan, Zhixin Huang, Chandana Nivarthi, Stephan Vogt:
The Problem with Real-World Novelty Detection - Issues in Multivariate Probabilistic Models. ACSOS-C 2021: 204-209
Informal and Other Publications
- 2022
- [i1]Chandana Priya Nivarthi:
Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems. CoRR abs/2203.05026 (2022)
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