SOTAVerified

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

Showing 63516400 of 6748 papers

TitleStatusHype
Probabilistic Programming with Gaussian Process Memoization0
Time-dependent scaling patterns in high frequency financial data0
Anomalous volatility scaling in high frequency financial data0
Distilling Knowledge from Deep Networks with Applications to Healthcare Domain0
Moving poselets: A discriminative and interpretable skeletal motion representation for action recognition0
Hierarchical Sparse Modeling: A Choice of Two Group Lasso Formulations0
Temporal Subspace Clustering for Human Motion Segmentation0
Learning Theory and Algorithms for Forecasting Non-stationary Time Series0
Minimax Time Series Prediction0
Bidirectional Recurrent Neural Networks as Generative Models0
GP Kernels for Cross-Spectrum Analysis0
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels0
Rate-Agnostic (Causal) Structure Learning0
Sequential visibility-graph motifs0
Recognizing Temporal Linguistic Expression Pattern of Individual with Suicide Risk on Social Media0
The Automatic Statistician: A Relational Perspective0
Black box variational inference for state space modelsCode0
Learning Representations Using Complex-Valued Nets0
Learning Representations from EEG with Deep Recurrent-Convolutional Neural NetworksCode0
Graph-based denoising for time-varying point clouds0
Probabilistic Segmentation via Total Variation Regularization0
Deep Kalman FiltersCode0
A genetic algorithm to discover flexible motifs with supportCode0
Signal Fluctuation Sensitivity: an improved metric for optimizing detection of resting-state fMRI networks0
Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling0
Granger Causality in Multi-variate Time Series using a Time Ordered Restricted Vector Autoregressive Model0
Instantaneous Modelling and Reverse Engineering of DataConsistent Prime Models in Seconds!0
Learning to Diagnose with LSTM Recurrent Neural Networks0
A Winner-Take-All Approach to Emotional Neural Networks with Universal Approximation Property0
Population size predicts lexical diversity, but so does the mean sea level - why it is important to correctly account for the structure of temporal data0
Prediction of Dynamical time Series Using Kernel Based Regression and Smooth Splines0
Linear-time Detection of Non-linear Changes in Massively High Dimensional Time Series0
Blitzkriging: Kronecker-structured Stochastic Gaussian Processes0
Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks0
Uncovering the evolution of non-stationary stochastic variables: the example of asset volume-price fluctuations0
Data-driven detrending of nonstationary fractal time series with echo state networksCode0
Accelerometer based Activity Classification with Variational Inference on Sticky HDP-SLDS0
Clustering Noisy Signals with Structured Sparsity Using Time-Frequency RepresentationCode0
Multifractal Flexibly Detrended Fluctuation Analysis0
Optimizing and Contrasting Recurrent Neural Network Architectures0
A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas0
Quantification in-the-wild: data-sets and baselines0
Detecting a trend change in cross-border epidemic transmission0
Dynamical spectral unmixing of multitemporal hyperspectral images0
Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly BenchmarkCode1
Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices0
p-Markov Gaussian Processes for Scalable and Expressive Online Bayesian Nonparametric Time Series Forecasting0
Conditional Risk Minimization for Stochastic Processes0
Quantifying Emergent Behavior of Autonomous RobotsCode0
Predicting Sector Index Movement with Microblogging Public Mood Time Series on Social Issues0
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Benchmark Results

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