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Time Series Analysis

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

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Showing 3701–3750 of 6748 papers

TitleStatusHype
Reservoir Computing Using Complex Systems—0
Reservoir Computing via Quantum Recurrent Neural Networks—0
Reservoir Computing with Diverse Timescales for Prediction of Multiscale Dynamics—0
Reservoir Computing with Magnetic Thin Films—0
Reservoir observers: Model-free inference of unmeasured variables in chaotic systems—0
Multi-Spatio-temporal Fusion Graph Recurrent Network for Traffic forecasting—0
Residual Networks as Flows of Velocity Fields for Diffeomorphic Time Series Alignment—0
Rethinking Attention Mechanism in Time Series Classification—0
Rethinking the constraints of multimodal fusion: case study in Weakly-Supervised Audio-Visual Video Parsing—0
Retrieval Based Time Series Forecasting—0
Revealing hidden dynamics from time-series data by ODENet—0
Reverse Engineering Chemical Reaction Networks from Time Series Data—0
Review of automated time series forecasting pipelines—0
Review of Clustering Methods for Functional Data—0
Review of Data-centric Time Series Analysis from Sample, Feature, and Period—0
Review of Time Series Forecasting Methods and Their Applications to Particle Accelerators—0
Revisited Large Language Model for Time Series Analysis through Modality Alignment—0
Revisiting Causality Inference in Memory-less Transition Networks—0
Revisiting clustering as matrix factorisation on the Stiefel manifold—0
Revisiting Deep Architectures for Head Motion Prediction in 360° Videos—0
Revisiting Inaccuracies of Time Series Averaging under Dynamic Time Warping—0
RF-Based Low-SNR Classification of UAVs Using Convolutional Neural Networks—0
RFID-based Article-to-Fixture Predictions in Real-World Fashion Stores—0
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise—0
Riemannian-geometry-based modeling and clustering of network-wide non-stationary time series: The brain-network case—0
RISE and DISE: Two Frameworks for Learning from Time Series with Missing Data—0
RiskFinder: A Sentence-level Risk Detector for Financial Reports—0
RiskLoc: Localization of Multi-dimensional Root Causes by Weighted Risk—0
Risk Management and Return Prediction—0
RLAD: Time Series Anomaly Detection through Reinforcement Learning and Active Learning—0
RNN-based Early Cyber-Attack Detection for the Tennessee Eastman Process—0
Roadmap on Signal Processing for Next Generation Measurement Systems—0
Road Surface Friction Prediction Using Long Short-Term Memory Neural Network Based on Historical Data—0
A Comprehensive Guide to CAN IDS Data & Introduction of the ROAD Dataset—0
Robust and efficient change point detection using novel multivariate rank-energy GoF test—0
Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection---Extended Version—0
Robust and fast heart rate variability analysis of long and noisy electrocardiograms using neural networks and images—0
Robust and Scalable Models of Microbiome Dynamics—0
Robust and Scalable Models of Microbiome Dynamics—0
Robust Anomaly Detection for Time-series Data—0
Robust Audio Anomaly Detection—0
Robust Augmentation for Multivariate Time Series Classification—0
Robust Clustering for Time Series Using Spectral Densities and Functional Data Analysis—0
Robust Constrained Multi-objective Evolutionary Algorithm based on Polynomial Chaos Expansion for Trajectory Optimization—0
Robust Domain-Free Domain Generalization with Class-aware Alignment—0
Robust Dominant Periodicity Detection for Time Series with Missing Data—0
Robust Forecasting for Robotic Control: A Game-Theoretic Approach—0
Robust Group Subspace Recovery: A New Approach for Multi-Modality Data Fusion—0
Robust guarantees for learning an autoregressive filter—0
Robustifying Markowitz—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47—Unverified
2GRU-D - APC (n = 1)F127.3—Unverified
3GRU-APC (n = 1)F125.7—Unverified
4GRU-DF122.5—Unverified
5GRUF122.3—Unverified
6GRU-SimpleF122.2—Unverified
7GRU-MeanF122.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51—Unverified
2ViT% Test Accuracy98.11—Unverified
3FlexTCN-4% Test Accuracy97.73—Unverified
4MatchboxNet% Test Accuracy97.4—Unverified
5CKCNN (100k)% Test Accuracy95.27—Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73—Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13—Unverified