Artificial general intelligence for medical imaging analysis
Large-scale Artificial General Intelligence (AGI) models, including Large Language Models
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …
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 …
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …
sustainable development by harnessing the power of cross-domain data fusion from diverse …
Controltraj: Controllable trajectory generation with topology-constrained diffusion model
Generating trajectory data is among promising solutions to addressing privacy concerns,
collection costs, and proprietary restrictions usually associated with human mobility …
collection costs, and proprietary restrictions usually associated with human mobility …
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
Deep learning for time series forecasting has seen significant advancements over the past
decades. However, despite the success of large-scale pre-training in language and vision …
decades. However, despite the success of large-scale pre-training in language and vision …
A survey on diffusion models for time series and spatio-temporal data
The study of time series data is crucial for understanding trends and anomalies over time,
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …
Position: What Can Large Language Models Tell Us about Time Series Analysis
Time series analysis is essential for comprehending the complexities inherent in various real-
world systems and applications. Although large language models (LLMs) have recently …
world systems and applications. Although large language models (LLMs) have recently …
Timedit: General-purpose diffusion transformers for time series foundation model
With recent advances in building foundation models for texts and video data, there is a surge
of interest in foundation models for time series. A family of models have been developed …
of interest in foundation models for time series. A family of models have been developed …
MM-Forecast: A Multimodal Approach to Temporal Event Forecasting with Large Language Models
We study an emerging and intriguing problem of multimodal temporal event forecasting with
large language models. Compared to using text or graph modalities, the investigation of …
large language models. Compared to using text or graph modalities, the investigation of …
A survey of spatio-temporal eeg data analysis: from models to applications
In recent years, the field of electroencephalography (EEG) analysis has witnessed
remarkable advancements, driven by the integration of machine learning and artificial …
remarkable advancements, driven by the integration of machine learning and artificial …