Summary of Federated Foundation Models on Heterogeneous Time Series, by Shengchao Chen et al.
Federated Foundation Models on Heterogeneous Time Seriesby Shengchao Chen, Guodong Long, Jing Jiang, Chengqi ZhangFirst…
Summary of Proactive Model Adaptation Against Concept Drift For Online Time Series Forecasting, by Lifan Zhao et al.
Proactive Model Adaptation Against Concept Drift for Online Time Series Forecastingby Lifan Zhao, Yanyan ShenFirst…
Summary of Adversarial Vulnerabilities in Large Language Models For Time Series Forecasting, by Fuqiang Liu et al.
Adversarial Vulnerabilities in Large Language Models for Time Series Forecastingby Fuqiang Liu, Sicong Jiang, Luis…
Summary of Modeling Latent Non-linear Dynamical System Over Time Series, by Ren Fujiwara et al.
Modeling Latent Non-Linear Dynamical System over Time Seriesby Ren Fujiwara, Yasuko Matsubara, Yasushi SakuraiFirst submitted…
Summary of Accurate Prediction Of Temperature Indicators in Eastern China Using a Multi-scale Cnn-lstm-attention Model, by Jiajiang Shen et al.
Accurate Prediction of Temperature Indicators in Eastern China Using a Multi-Scale CNN-LSTM-Attention modelby Jiajiang Shen,…
Summary of Advancing Clinical Trial Outcomes Using Deep Learning and Predictive Modelling: Bridging Precision Medicine and Patient-centered Care, by Sydney Anuyah et al.
Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered…
Summary of Lms-autotsf: Learnable Multi-scale Decomposition and Integrated Autocorrelation For Time Series Forecasting, by Ibrahim Delibasoglu and Sanjay Chakraborty and Fredrik Heintz
LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecastingby Ibrahim Delibasoglu, Sanjay Chakraborty,…
Summary of Tube Loss: a Novel Approach For Prediction Interval Estimation and Probabilistic Forecasting, by Pritam Anand et al.
Tube Loss: A Novel Approach for Prediction Interval Estimation and probabilistic forecastingby Pritam Anand, Tathagata…
Summary of Food For Thought: How Can Machine Learning Help Better Predict and Understand Changes in Food Prices?, by Kristina L. Kupferschmidt et al.
Food for thought: How can machine learning help better predict and understand changes in food…
Summary of Measuring Pre-training Data Quality Without Labels For Time Series Foundation Models, by Songkang Wen et al.
Measuring Pre-training Data Quality without Labels for Time Series Foundation Modelsby Songkang Wen, Vasilii Feofanov,…