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Showing 3501–3525 of 9169 papers

TitleStatusHype
Explaining Deep Learning Models for Age-related Gait Classification based on time series accelerationCode0
Data-Guided Regulator for Adaptive Nonlinear Control—0
TimeSQL: Improving Multivariate Time Series Forecasting with Multi-Scale Patching and Smooth Quadratic Loss—0
Self-Distilled Representation Learning for Time Series—0
Link Streams as a Generalization of Graphs and Time Series—0
SEA++: Multi-Graph-based High-Order Sensor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation—0
Informative Priors Improve the Reliability of Multimodal Clinical Data Classification—0
Growth-rate distributions of gut microbiota time series—0
A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series—0
Identifying Systems with Symmetries using Equivariant Autoregressive Reservoir Computers—0
Evolving Domain Adaptation of Pretrained Language Models for Text Classification—0
A Multimodal Dataset of 21,412 Recorded Nights for Sleep and Respiratory Research—0
Measure of Dependence for Financial Time-Series—0
Structured Estimation of Heterogeneous Time Series—0
Approaching adverse event detection utilizing transformers on clinical time-series—0
On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series—0
Modeling Complex Disease Trajectories using Deep Generative Models with Semi-Supervised Latent ProcessesCode0
Application Research of Spline Interpolation and ARIMA in the Field of Stock Market Forecasting—0
USLR: an open-source tool for unbiased and smooth longitudinal registration of brain MRCode0
PEMS: Pre-trained Epidemic Time-series Models—0
Mixture of Coupled HMMs for Robust Modeling of Multivariate Healthcare Time SeriesCode0
Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks—0
Revisiting Cont's Stylized Facts for Modern Stock Markets—0
A Hypothesis on Good Practices for AI-based Systems for Financial Time Series Forecasting: Towards Domain-Driven XAI Methods—0
Estimating optical vegetation indices and biophysical variables for temperate forests with Sentinel-1 SAR data using machine learning techniques: A case study for CzechiaCode0
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