37 citations · 54 across the 27 of their papers we have counts for
8 papers · 1 filter
Assessing Pre-Trained Models for Transfer Learning Through Distribution of Spectral Components
Tengxue Zhang, Yang Shu, Xinyang Chen +3
Pre-trained model assessment for transfer learning aims to identify the optimal candidate for the downstream tasks from a model hub, without the need of time-consuming fine-tuning.…
MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast
Shiyan Hu, Kai Zhao, Xiangfei Qiu +4
Many methods have been proposed for unsupervised time series anomaly detection. Despite some progress, research on predicting future anomalies is still relatively scarce. Predictin…
Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning
Kai Zhao, Zhihao Zhuang, Chenjuan Guo +3
Time series anomaly prediction plays an essential role in many real-world scenarios, such as environmental prevention and prompt maintenance of cyber-physical systems. However, exi…
Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer
Yihang Wang, Yuying Qiu, Peng Chen +6
With the growing availability of multi-domain time series data, there is an increasing demand for general forecasting models pre-trained on multi-source datasets to support diverse…
Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders
Qichao Shentu, Beibu Li, Kai Zhao +5
Time series anomaly detection plays a vital role in a wide range of applications. Existing methods require training one specific model for each dataset, which exhibits limited gene…
A Unified Replay-based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data
Hao Miao, Yan Zhao, Chenjuan Guo +5
The widespread deployment of wireless and mobile devices results in a proliferation of spatio-temporal data that is used in applications, e.g., traffic prediction, human mobility m…
QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models -- Extended Version
David Campos, Bin Yang, Tung Kieu +3
We are witnessing an increasing availability of streaming data that may contain valuable information on the underlying processes. It is thus attractive to be able to deploy machine…
Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
Peng Chen, Yingying Zhang, Yunyao Cheng +5
Transformers for time series forecasting mainly model time series from limited or fixed scales, making it challenging to capture different characteristics spanning various scales.…