Results 71 to 80 of about 18,244,857 (290)

Multivariate Financial Time-Series Prediction With Certified Robustness

IEEE Access, 2020
The futures market's forecasts are significant to investors and policymakers, where the application of deep learning approaches to finance has received a great deal of attention.
Hui Li, Yunpeng Cui, Shuo Wang, Juan Liu, Jinyuan Qin, Yilin Yang   +5 more
doaj   +1 more source

Revisiting Attention for Multivariate Time Series Forecasting

Proceedings of the AAAI Conference on Artificial Intelligence
Current Transformer methods for Multivariate Time-Series Forecasting (MTSF) are all based on the conventional attention mechanism. They involve sequence embedding and performing a linear projection for Q, K, and V, and then computing attention within this latent space.
openaire   +2 more sources

The vector innovation structural time series framework: a simple approach to multivariate forecasting [PDF]

The vector innovation structural time series framework is proposed as a way of modelling a set of related time series. Like all multi-series approaches, the aim is to exploit potential inter-series dependencies to improve the fit and forecasts.
Rob J. Hyndman, Ashton de Silva, Ralph D. Snyder   +2 more
core  

HMGCR‐Driven Cholesterol Metabolism Promotes Osteoarthritis Progression by Accelerating Synovial Fibroblast Senescence

Advanced Science, EarlyView.
In the pathological context of osteoarthritis (OA), the phosphorylation of AKT1 at Ser473 enhances its binding to Lys140 of Insig1, which facilitates the formation of AKT1–Insig1 complex. Subsequently, the activation of AKT1 promotes the phosphorylation of Insig1 at Ser189, potentially enhancing the dissociation of Insig1 from sterol regulatory element‑
Xiaoqi Zhang, Siru Zhou, Xi Liu, Wei Xiang, Xiuqin Peng, Yu Tian, Song Li, Hailin Wang, Bo Liao, Shunzheng Fang, Runze Jin, Jinhui Wu, Chuanqing Bai, Wei Zhang, Bo Huang, Bingfei Li, Lifeng Chen, Lin Chen, Bin Zhang, Zhenhong Ni   +19 more
wiley   +1 more source

Multi-Scale Transformer Pyramid Networks for Multivariate Time Series Forecasting

IEEE Access
Multivariate Time Series (MTS) forecasting entails the intricate process of modeling temporal dependencies within historical data records. Transformers have demonstrated remarkable performance in MTS forecasting due to their capability to capture long ...
Yifan Zhang, Rui Wu, Sergiu M. Dascalu, Frederick C. Harris   +3 more
doaj   +1 more source

25 Years of IIF Time Series Forecasting: A Selective Review [PDF]

We review the past 25 years of time series research that has been published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982-1985; International Journal of Forecasting 1985-2005). During this period, over one
Jan G. De Gooijer, Rob J. Hyndman
core  

Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations

Advanced Science, EarlyView.
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford, Matthew Tamasi, Elena Di Mare, Adam J. Gormley   +3 more
wiley   +1 more source

Multivariate Segment Expandable Encoder-Decoder Model for Time Series Forecasting

IEEE Access
Accurate time series forecasting is critical in a variety of fields, including transportation, weather prediction, energy management, infrastructure monitoring, and finance.
Yanhong Li, David C. Anastasiu
doaj   +1 more source

Systemic Nanomechanical Single‐Cell Profiling Reveals Mechanophenotype Transitions Under Therapeutic Perturbation

Advanced Science, EarlyView.
Single‐cell mechanomics demonstrates that pharmacological perturbation changes cytoskeletal and cortical structure, suppressing cancer cell invasiveness. By integrating atomic force microscopy (AFM)‐based cortical measurements with stimulated emission depletion (STED)‐resolved adhesion and cytoskeletal organization, this approach identifies nanoscale ...
Minhee Ku, Jinwon Kwon, Nara Yoon, Hyung Kwon Byeon, Jaemoon Yang   +4 more
wiley   +1 more source

Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand [PDF]

In this paper we propose a new set of multivariate stochastic models that capture time varying seasonality within the vector innovations structural time series (VISTS) framework.
Ashton de Silva, George Athanasopoulos
core