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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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3801–3850 of 6748 papers

TitleStatusHype
Recurrent convolutional neural network for the surrogate modeling of subsurface flow simulation—0
MIA-Prognosis: A Deep Learning Framework to Predict Therapy ResponseCode0
Multivariate Temporal Autoencoder for Predictive Reconstruction of Deep Sequences—0
Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning—0
Gene Regulatory Network Inference with Latent Force Models—0
Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices—0
Conditional Generative Adversarial Networks to Model Urban Outdoor Air Pollution—0
Direct Signal Separation Via Extraction of Local Frequencies with Adaptive Time-Varying Parameters—0
Bayesian Feature Selection in Joint Quantile Time Series Analysis—0
TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series—0
Mining and modeling complex leadership-followership dynamics of movement data—0
From Time Series to Euclidean Spaces: On Spatial Transformations for Temporal Clustering—0
Modifying the Symbolic Aggregate Approximation Method to Capture Segment Trend Information—0
Extreme-SAX: Extreme Points Based Symbolic Representation for Time Series Classification—0
Active Tuning—0
An Evaluation of Classification Methods for 3D Printing Time-Series Data—0
Citation Sentiment Changes AnalysisCode0
Universal time-series forecasting with mixture predictors—0
Concurrent Neural Network : A model of competition between times seriesCode0
AAMDRL: Augmented Asset Management with Deep Reinforcement Learning—0
Uncovering Feature Interdependencies in High-Noise Environments with Stepwise Lookahead Decision Forests—0
Few-shot Learning for Time-series Forecasting—0
A Wavelet-CNN-LSTM Model for Tailings Pond Risk Prediction—0
EEG to fMRI Synthesis: Is Deep Learning a candidate?—0
Go with the FLOW: Visualizing spatiotemporal dynamics in optical widefield calcium imaging—0
Anomaly Detection and Sampling Cost Control via Hierarchical GANs—0
Neural CDEs for Long Time Series via the Log-ODE Method—0
Inferring Global Dynamics Using a Learning Machine—0
Forecasting Short-term load using Econometrics time series model with T-student Distribution—0
Semi-Supervised Learning for In-Game Expert-Level Music-to-Dance Translation—0
Decision-Aware Conditional GANs for Time Series Data—0
Piece-wise Matching Layer in Representation Learning for ECG Classification—0
Deep Learning based Covert Attack Identification for Industrial Control Systems—0
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting—0
Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data—0
A first econometric analysis of the CRIX family—0
Cloud Cover Nowcasting with Deep Learning—0
N-BEATS neural network for mid-term electricity load forecastingCode0
Limit Theorems for Factor Models—0
A Linear Transportation L^p Distance for Pattern Recognition—0
CoVaR with volatility clustering, heavy tails and non-linear dependence—0
Vertical Power Flow Forecast with LSTMs Using Regular Training Update Strategies—0
Survey of explainable machine learning with visual and granular methods beyond quasi-explanations—0
A Sequential Modelling Approach for Indoor Temperature Prediction and Heating Control in Smart Buildings—0
A Time Series Data Analysis of Indian Commercial Dynamism—0
Breaking Symmetries of the Reservoir Equations in Echo State Networks—0
Mapping horizontal and vertical urban densification in Denmark with Landsat time-series from 1985 to 2018: a semantic segmentation solution—0
Subjective Metrics-based Cloud Market Performance Prediction—0
From Static to Dynamic Node Embeddings—0
Resilient In-Season Crop Type Classification in Multispectral Satellite Observations using Growth Stage NormalizationCode0
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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