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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 4051–4075 of 6748 papers

TitleStatusHype
A Multi-Variate Triple-Regression Forecasting Algorithm for Long-Term Customized Allergy Season Prediction—0
Temporal-Framing Adaptive Network for Heart Sound Segmentation without Prior Knowledge of State Duration—0
Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso—0
Social Media Information Sharing for Natural Disaster Response—0
Layer-wise training convolutional neural networks with smaller filters for human activity recognition using wearable sensors—0
Optimizing Temporal Convolutional Network inference on FPGA-based accelerators—0
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University—0
On a computationally-scalable sparse formulation of the multidimensional and non-stationary maximum entropy principleCode0
Knowledge Enhanced Neural Fashion Trend ForecastingCode0
XEM: An Explainable-by-Design Ensemble Method for Multivariate Time Series ClassificationCode1
Joint Multi-Dimensional Model for Global and Time-Series Annotations—0
Approaches and Applications of Early Classification of Time Series: A Review—0
Deep Recurrent Model for Individualized Prediction of Alzheimer's Disease ProgressionCode1
Deep convolutional generative adversarial networks for traffic data imputation encoding time series as images—0
P2ExNet: Patch-based Prototype Explanation Network—0
DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data—0
Tail Granger causalities and where to find them: extreme risk spillovers vs. spurious linkages—0
Cost-Effective Bad Synchrophasor Data Detection Based on Unsupervised Time Series Data Analytics—0
Multivariate Time Series Forecasting with Transfer Entropy GraphCode1
If You Like It, GAN It. Probabilistic Multivariate Times Series Forecast With GANCode0
Teaching Recurrent Neural Networks to Modify Chaotic Memories by Example—0
SleepPoseNet: Multi-View Learning for Sleep Postural Transition Recognition Using UWBCode1
On time series representations for multi-label NILMCode1
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data—0
Deep ConvLSTM with self-attention for human activity decoding using wearablesCode1
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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