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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 151–200 of 6748 papers

TitleStatusHype
Cost-effective Interactive Attention Learning with Neural Attention ProcessesCode1
COT-GAN: Generating Sequential Data via Causal Optimal TransportCode1
Copula Conformal Prediction for Multi-step Time Series ForecastingCode1
Convolution-enhanced Evolving Attention NetworksCode1
Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal BootstrappingCode1
Contrastive Domain Adaptation for Time-Series via Temporal MixupCode1
Contrastive Neural Processes for Self-Supervised LearningCode1
Contrastive Learning for Unsupervised Domain Adaptation of Time SeriesCode1
Convolutional Radio Modulation Recognition NetworksCode1
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential EquationsCode1
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-SeriesCode1
Random Dilated Shapelet Transform: A New Approach for Time Series ShapeletsCode1
Counterfactual Explanations for Machine Learning on Multivariate Time Series DataCode1
Construe: a software solution for the explanation-based interpretation of time seriesCode1
Neural graphical modelling in continuous-time: consistency guarantees and algorithmsCode1
Continual Transformers: Redundancy-Free Attention for Online InferenceCode1
Conformal Time-series ForecastingCode1
Conformal prediction set for time-seriesCode1
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural NetworksCode1
Continuous Latent Process FlowsCode1
The Signature Kernel is the solution of a Goursat PDECode1
Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetCode1
Conditional GAN for timeseries generationCode1
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task LearningCode1
Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image RepresentationCode1
Classification of Long Sequential Data using Circular Dilated Convolutional Neural NetworksCode1
Conditional Sig-Wasserstein GANs for Time Series GenerationCode1
Continuous-Time Deep Glioma Growth ModelsCode1
COVID-19 Data Analysis and Forecasting: Algeria and the WorldCode1
Deep ConvLSTM with self-attention for human activity decoding using wearablesCode1
A Deep Learning Approach to Analyzing Continuous-Time SystemsCode1
Changing Fashion CulturesCode1
Chaos as an interpretable benchmark for forecasting and data-driven modellingCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
Causal Forecasting:Generalization Bounds for Autoregressive ModelsCode1
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-valuesCode1
CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-LevelCode1
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking ApplicationsCode1
catch22: CAnonical Time-series CHaracteristicsCode1
Data-driven discovery of intrinsic dynamicsCode1
Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant RepresentationCode1
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time seriesCode1
Classification of Periodic Variable Stars with Novel Cyclic-Permutation Invariant Neural NetworksCode1
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware DetectionCode1
Closed-Form Diffeomorphic Transformations for Time Series AlignmentCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Color-aware two-branch DCNN for efficient plant disease classificationCode1
Compatible deep neural network framework with financial time series data, including data preprocessor, neural network model and trading strategyCode1
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural NetworksCode1
Calibration of Google Trends Time SeriesCode1
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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