Foundation models for time series analysis: A tutorial and survey
Time series analysis stands as a focal point within the data mining community, serving as a
cornerstone for extracting valuable insights crucial to a myriad of real-world applications …
cornerstone for extracting valuable insights crucial to a myriad of real-world applications …
[HTML][HTML] Data augmentation techniques in time series domain: a survey and taxonomy
With the latest advances in deep learning-based generative models, it has not taken long to
take advantage of their remarkable performance in the area of time series. Deep neural …
take advantage of their remarkable performance in the area of time series. Deep neural …
One fits all: Power general time series analysis by pretrained lm
Although we have witnessed great success of pre-trained models in natural language
processing (NLP) and computer vision (CV), limited progress has been made for general …
processing (NLP) and computer vision (CV), limited progress has been made for general …
Transformers in time series: A survey
Transformers have achieved superior performances in many tasks in natural language
processing and computer vision, which also triggered great interest in the time series …
processing and computer vision, which also triggered great interest in the time series …
Time-llm: Time series forecasting by reprogramming large language models
Time series forecasting holds significant importance in many real-world dynamic systems
and has been extensively studied. Unlike natural language process (NLP) and computer …
and has been extensively studied. Unlike natural language process (NLP) and computer …
Deep learning for time series classification and extrinsic regression: A current survey
Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …
learning tasks. Deep learning has revolutionized natural language processing and computer …
Hyporadise: An open baseline for generative speech recognition with large language models
Advancements in deep neural networks have allowed automatic speech recognition (ASR)
systems to attain human parity on several publicly available clean speech datasets …
systems to attain human parity on several publicly available clean speech datasets …
Large models for time series and spatio-temporal data: A survey and outlook
Temporal data, notably time series and spatio-temporal data, are prevalent in real-world
applications. They capture dynamic system measurements and are produced in vast …
applications. They capture dynamic system measurements and are produced in vast …
A survey on time-series pre-trained models
Time-Series Mining (TSM) is an important research area since it shows great potential in
practical applications. Deep learning models that rely on massive labeled data have been …
practical applications. Deep learning models that rely on massive labeled data have been …
Watermarking for out-of-distribution detection
Abstract Out-of-distribution (OOD) detection aims to identify OOD data based on
representations extracted from well-trained deep models. However, existing methods largely …
representations extracted from well-trained deep models. However, existing methods largely …