The Problem with Real-World Novelty Detection - Issues in Multivariate Probabilistic Models. - Christian Gruhl; Abdul Hannan; Zhixin Huang; Chandana Nivarthi; Stephan Vogt (ACSOS-C, 2021)

Unified Autoencoder with Task Embeddings for Multi-Task Learning in Renewable Power Forecasting. - Chandana Priya Nivarthi; Stephan Vogt; Bernhard Sick (ICMLA, 2022)

Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems. - Chandana Priya Nivarthi (CoRR, 2022)

Towards Few-Shot Time Series Anomaly Detection with Temporal Attention and Dynamic Thresholding. - Chandana Priya Nivarthi; Bernhard Sick (ICMLA, 2023)

Multi-Task Representation Learning for Renewable-Power Forecasting: A Comparative Analysis of Unified Autoencoder Variants and Task-Embedding Dimensions. - Chandana Priya Nivarthi; Stephan Vogt; Bernhard Sick (Mach. Learn. Knowl. Extr., 2023)

Time-Series Representation Learning via Heterogeneous Spatial-Temporal Contrasting for Remaining Useful Life Prediction. - Zhixin Huang; Yujiang He; Chandana Priya Nivarthi; Bernhard Sick; Christian Gruhl (ICPR (27), 2024)

Spatial-Temporal Attention Graph Neural Network with Uncertainty Estimation for Remaining Useful Life Prediction. - Zhixin Huang; Yujiang He; Chandana Priya Nivarthi; Christian Gruhl; Bernhard Sick (IJCNN, 2024)

Multi-Task Representation Learning with Temporal Attention for Zero-Shot Time Series Anomaly Detection. - Chandana Priya Nivarthi; Zhixin Huang; Christian Gruhl; Bernhard Sick (IJCNN, 2024)