Results 61 to 70 of about 56,489 (266)

Bootstrapping periodically autoregressive models [PDF]

ESAIM: Probability and Statistics, 2017
The main objective of this paper is to establish the residual and the wild bootstrap procedures for periodically autoregressive models. We use the least squares estimators of model’s parameters and generate their bootstrap equivalents. We prove that the bootstrap procedures for causal periodic autoregressive time series with finite fourth moments are ...
Ciołek, Gabriela, Potorski, Paweł
openaire   +2 more sources

CLRe: A Synergistic Dual‐Engine Framework for One‐Step Retrosynthesis Prediction

Advanced Science, EarlyView.
CLRe uses a contrastive difficulty score to order pretrained seq2seq fine‐tuning for retrosynthesis. Reaction embeddings define the ranking score, and a cumulative easy‐to‐hard schedule expands from the easiest subset to the full training set while earlier examples remain active.
Tianhao Su, Xitao Wang, Musen Li, Guanhua Qin, Shunbo Hu, Tong‐Yi Zhang   +5 more
wiley   +1 more source

Exploring the Frontier: Generative AI Applications in Online Consumer Behavior Analytics

Management Letters/Cuadernos de Gestión
This paper presents a systematic review of the application of generative artificial intelligence (AI) in online consumer behavior analytics (OCBA). With the advent of e-commerce and social media, consumer behavior increasingly occurs online, generating ...
Takuma Kimura
doaj   +1 more source

CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model

Advanced Science, EarlyView.
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang, Yuqi Zhang, Xuzhe Zhao, Yansong Tang, Kaichen Dong   +4 more
wiley   +1 more source

Groundwater Rise Sustains the World's Largest Alpine Water System Under Global Warming

Advanced Science, EarlyView.
Shallow groundwater depth (SGWD) across the non‐permafrost plains of the Qinghai–Xizang Plateau decreased at averagely 0.02 m year−1, adding 31.44 Gt of freshwater storage from 2000 to 2020 and sustaining ∼53 500 km2 of alpine ecosystems. A vadose‐zone capacity of 426.6 Gt reveals these aquifers as promising reservoirs, highlighting groundwater's ...
Jianqing Du, Zhixiang Niu, Yanfen Wang, Shirui Zhou, Youqing Yang, Xiang Wei, Haishan Niu, Yitao Zhang, Anquan Xia, Yali Liu, Yanbin Hao, Kai Xue, Bingfang Wu, Xinquan Zhao, Tandong Yao, Yiyu Chen   +15 more
wiley   +1 more source

Bivariate binomial autoregressive models

Journal of Multivariate Analysis, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Manuel G. Scotto, Christian H. Weiß, Maria Eduarda Silva, Isabel Pereira   +3 more
openaire   +2 more sources

Computationally Evidence‐Grounded Sequence‐First Design of Peptide Binders

Advanced Science, EarlyView.
BOND‐PEP enables controllable, sequence‐first peptide binder design by grounding generation in binding evidence retrieved for each target. It uses topology‐conditioned message passing to integrate relevant peptide examples with the target protein sequence, forming a residue‐level representation that guides the generation of diverse, target‐specific ...
Wenze Ding
wiley   +1 more source

A Site‐Aware Representation Learning Framework For Unified Molecular Interaction Modeling and Generative Design

Advanced Science, EarlyView.
MolDBG is a site‐aware, sequence‐only framework that unifies drug‐target affinity prediction, binding‐site identification, and affinity‐conditioned molecular generation for structured proteins. Guided by multi‐task binding‐site supervision, it aligns interaction‐critical residues before learning drug‐target representations and simultaneously infers ...
Gang Luo, Qianqian Zhang, Chenhao Wang, Zhiheng Yi, Alex Jinpeng Wang, Jing Tang, Min Li   +6 more
wiley   +1 more source

Universal Battery Capacity Degradation Forecasting Driven by Foundation Models Across Diverse Chemistries and Conditions

Advanced Science, EarlyView.
A unified time‐series forecasting framework learns transferable battery capacity‐degradation patterns from 20 heterogeneous datasets spanning chemistries, formats, temperatures, and cycling conditions. A single model delivers competitive predictions on both known and previously unseen datasets, while physics‐guided representation learning improves ...
Joey Chan, Huan Wang, Zhen Chen, Haoyu Pan, Wei Wu, Zirong Wang, Ershun Pan, Min Xie, Lifeng Xi   +8 more
wiley   +1 more source

Enhanced High Dimensionality and the Information Processing Capacity in Interfered Spin Wave‐Based Reservoir Computing, Achieved With Eight Detectors

Advanced Electronic Materials, EarlyView.
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa, Wataru Namiki, Daiki Nishioka, Maki Nishimura, Ryo Iguchi, Kazuya Terabe, Takashi Tsuchiya   +6 more
wiley   +1 more source