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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 3901–3950 of 6748 papers

TitleStatusHype
Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series—0
LAVARNET: Neural Network Modeling of Causal Variable Relationships for Multivariate Time Series Forecasting—0
Travel time prediction for congested freeways with a dynamic linear model—0
A Review of Wind Speed and Wind Power Forecasting Techniques—0
Weak error rates for option pricing under linear rough volatilityCode0
MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scales—0
Data Anomaly Detection for Structural Health Monitoring of Bridges using Shapelet Transform—0
The Computational Capacity of LRC, Memristive and Hybrid Reservoirs—0
Convolutional Neural Network-Bagged Decision Tree: A hybrid approach to reduce electric vehicle's driver's range anxiety by estimating energy consumption in real-time—0
Effects of Correlated Noise on the Performance of Persistence Based Dynamic State Detection Methods—0
Benchmarking adversarial attacks and defenses for time-series data—0
Computer Model Calibration with Time Series Data using Deep Learning and Quantile Regression—0
Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution LearningCode0
Fast Partial Fourier Transform—0
Learning Compact Physics-Aware Delayed Photocurrent Models Using Dynamic Mode Decomposition—0
DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data—0
Koopman Mode Decomposition of Oscillatory Temperature Field inside a Room—0
Forecasting with Multiple SeasonalityCode0
Investigation of Flash Crash via Topological Data Analysis—0
Hybrid Deep Neural Networks to Infer State Models of Black-Box SystemsCode0
Gesture Recognition from Skeleton Data for Intuitive Human-Machine Interaction—0
Automated Model Selection for Time-Series Anomaly Detection—0
Prediction of Hilbertian autoregressive processes : a Recurrent Neural Network approach—0
Photonic reservoir computer based on frequency multiplexing—0
Comparative Computational Analysis of Global Structure in Canonical, Non-Canonical and Non-Literary Texts—0
ATM Cash demand forecasting in an Indian Bank with chaos and deep learning—0
Seasonal-adjustment Based Feature Selection Method for Large-scale Search Engine Logs—0
DeepSTCL: A Deep Spatio-temporal ConvLSTM for Travel Demand Prediction—0
Spectral independent component analysis with noise modeling for M/EEG source separation—0
Evaluating Machine Learning Models for the Fast Identification of Contingency Cases—0
Reinforcement Learning based dynamic weighing of Ensemble Models for Time Series Forecasting—0
Exact Tests for Offline Changepoint Detection in Multichannel Binary and Count Data with Application to Networks—0
The Canonical Interval Forest (CIF) Classifier for Time Series Classification—0
Reforming the State-Based Forward Guidance through Wage Growth Rate Threshold: Evidence from FRB/US SimulationsCode0
MTHetGNN: A Heterogeneous Graph Embedding Framework for Multivariate Time Series Forecasting—0
Augmenting Neural Differential Equations to Model Unknown Dynamical Systems with Incomplete State InformationCode0
Selecting Data Adaptive Learner from Multiple Deep Learners using Bayesian Networks—0
A Formally Robust Time Series Distance Metric—0
Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting—0
RTFN: Robust Temporal Feature Network—0
Long vs Short Time Scales: the Rough Dilemma and Beyond—0
Generative Adversarial Networks for Spatio-temporal Data: A Survey—0
Predicting Future Sales of Retail Products using Machine Learning—0
Extension of causal decomposition in the mutual complex dynamic process—0
Deep Neural Networks for automatic extraction of features in time series satellite images—0
Wavelet Denoising and Attention-based RNN-ARIMA Model to Predict Forex Price—0
Gait complexity assessed by detrended fluctuation analysis is sensitive to inconsistencies in stride time series: A modeling study—0
Neural Network-based Automatic Factor Construction—0
Image Processing Tools for Financial Time Series Classification—0
Spectral Processing of COVID-19 Time-Series DataCode0
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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