AI Briefing#time-series-forecasting
The latest AI and developer news about #time-series-forecasting, with the original source and a short summary.
The latest AI and developer news about #time-series-forecasting, with the original source and a short summary.
The ensemble achieves a MASE of 0.683 on GIFT-Eval, outperforming its best individual member without requiring fine-tuning.
The paper introduces feature-splitting and physical sparsity priors to enable hierarchical DSR models to predict bifurcations and unseen dynamical regimes without explicit control parameter knowledge.
Google Research has released TimesFM-3, a 330-million-parameter time-series foundation model that predicts multivariate data and covariates in a single forward pass.
Google has released TimesFM-3, a foundation model for multivariate time series forecasting based on 330 billion parameters.
This introduces graph-based Spatio-temporal Time-series Forecasting research presented at ICML 2021.
This introduces the MAMA framework, which maximizes forecasting performance by leveraging multi-resolution information in time series data.
LG AI Research presented the MAMA framework at ICASSP 2023, maximizing time series forecasting performance.
LG AI Research's demand forecasting squad achieved results winning awards in 3 categories at the M6 conference held in New York.
LG AI Research's demand forecasting squad achieved award-winning results in 3 categories at the M6 forecasting competition held in New York.
Introduces innovative time series forecasting AI models presented at ICLR 2024 and LG AI Research's research vision.
It introduces the methodologies and technical characteristics of innovative time series forecasting models presented at ICLR 2024.
LG AI Research proposed AIR, a multimodal time series forecasting technology that reflects the characteristics of time series data and text data.
LG AI Research presented the VarDrop algorithm at AAAI-25, which reduces variate redundancy in time-series data to improve training efficiency.
LG AI Research proposed the VarDrop algorithm, which maximizes the training efficiency of time series forecasting models by reducing redundancy among variates.
LG AI Research unveiled EXAONE BI, a finance-specialized AI agent that performs corporate analysis and portfolio optimization.
LG AI Research developed EXAONE BI, a financial solution based on the corporate analysis agent GanphA.
Google researchers proposed Nexus, a multi-agent time-series forecasting framework that simultaneously processes numerical data and textual context.
This introduces the TopoPrimer framework, which improves forecasting accuracy by leveraging the global topological structure of time-series data as an input.
Datadog released Toto 2.0, ranging from 4m to 2.5B parameters, demonstrating clear scaling effects.
Google Research has released **TimesFM 2.5**, a foundation model for time series forecasting.
A roundup of Amazon Science's 10 most-viewed blog posts of 2025, organized by topic.