Results 61 to 70 of about 18,244,857 (290)

BackTime: Backdoor Attacks on Multivariate Time Series Forecasting

Advances in Neural Information Processing Systems 37
23 pages.
Xiao Lin 0016, Zhining Liu 0002, Dongqi Fu, Ruizhong Qiu, Hanghang Tong   +4 more
openaire   +4 more sources

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

Multivariate Time Series Forecasting Method Combining Spatiotemporal and Kolmogorov-Arnold Networks [PDF]

Jisuanji gongcheng
Existing time series forecasting methods fail to fully consider the spatiotemporal dependencies among variables, which hinders the improvement of forecasting accuracy. Spatial modeling methods based on Graph Neural Networks (GNN) also have limitations in
JIAO Luyao, YANG Xiaoya, MENG Yaofei, LIU Songhua
doaj   +1 more source

A Machine Vision‐Guided Microphysiological Platform With Automated Microfluidics Enables Longitudinal Biomarker Monitoring and Emulation of Translationally Relevant Exposure Scenarios

Advanced Science, EarlyView.
A pneumatically actuated multi‐tissue microphysiological system is integrated with AI‐based machine vision and automatic sampling and replenishment systems. The platform allows for the emulation of translationally relevant long‐term pharmacokinetic exposure scenarios for multiple weeks while enabling longitudinal monitoring of response biomarkers ...
Jibbe Keulen, Yi Zhong, Laura Dangel, Sonia Youhanna, Reza Zandi Shafagh, Jinhye Ryu, Domnica‐Gabriela Gurau, Mathias Haag, Thomas E. Mürdter, Yingxin Liang, Iro Beligiani, Nicole Ziegler, Sabine Willems, Nayere Taebnia, Wouter van der Wijngaart, Volker M. Lauschke   +15 more
wiley   +1 more source

Channel-Wise Retrieval for Multivariate Time Series Forecasting

ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Multivariate time series forecasting often struggles to capture long-range dependencies due to fixed lookback windows. Retrieval-augmented forecasting addresses this by retrieving historical segments from memory, but existing approaches rely on a channel-agnostic strategy that applies the same references to all variables.
Junhyeok Kang, Jun Seo, Soyeon Park, Sangjun Han, Seohui Bae, Hyeokjun Choe, Soonyoung Lee   +6 more
openaire   +3 more sources

Recursive Identification. Estimation and Forecasting of Multivariate Time-series

IFAC Proceedings Volumes, 1988
Abstract The paper describes a new, fully recursive method for identifying, estimat-ing and forecasting multivariate (vector) time-series. Any low frequency (trend) components associated with each of the elements of the vector time-series are first removed by recursive, fixed interval smoothing based on generalised random walk (GRW) models; while the
Ng, CN, Young, PC, Wang, C
openaire   +2 more sources

Robust exponential smoothing of multivariate time series. [PDF]

Multivariate time series may contain outliers of different types. In presence of such outliers, applying standard multivariate time series techniques becomes unreliable. A robust version of multivariate exponential smoothing is proposed.
Croux, Christophe, Gelper, Sarah, Mahieu, Koen   +2 more
core  

Targeting GALNT7 Disrupts the TAZ O‐GalNAcylation Feedback Loop to Suppress Gallbladder Cancer Progression

Advanced Science, EarlyView.
Aberrant GALNT7‐mediated O‐GalNAcylation stabilizes TAZ to drive gallbladder cancer progression through a feed‐forward transcriptional loop. Structure‐based screening identifies Olaparib as a potent GALNT7 antagonist that disrupts this oncogenic axis, providing an immediate therapeutic strategy for this aggressive malignancy.
Peng Qiu, Ming Zhang, Yunxiang Feng, Yibo Deng, Kai Zhao, Xiangyu Li, Yun Lu, Li Tian, Tao Yang, Wei Yao, Jianming Wang, Zhengdong Deng   +11 more
wiley   +1 more source

STDNet: A Spatio-Temporal Decomposition Neural Network for Multivariate Time Series Forecasting

Tsinghua Science and Technology
Long-term multivariate time series forecasting is an important task in engineering applications. It helps grasp the future development trend of data in real-time, which is of great significance for a wide variety of fields.
Zhuolun Jiang, Zefei Ning, Hao Miao, Li Wang   +3 more
doaj   +1 more source