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

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Showing 2651–2700 of 6748 papers

TitleStatusHype
FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable StocksCode1
On the benefits of maximum likelihood estimation for Regression and Forecasting—0
On Contrastive Representations of Stochastic ProcessesCode1
ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative ModelsCode1
Pre-treatment of outliers and anomalies in plant data: Methodology and case study of a Vacuum Distillation Unit—0
Minimax Estimation of Partially-Observed Vector AutoRegressionsCode0
Voice2Series: Reprogramming Acoustic Models for Time Series ClassificationCode1
SCINet: Time Series Modeling and Forecasting with Sample Convolution and InteractionCode1
Multi-Modal Prototype Learning for Interpretable Multivariable Time Series Classification—0
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICACode1
Adaptive Visibility Graph Neural Network and It's Application in Modulation Classification—0
Trend-Following Strategies via Dynamic Momentum Learning—0
Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL—0
Adversarial Attacks on Deep Models for Financial Transaction RecordsCode0
Faster than LASER -- Towards Stream Reasoning with Deep Neural Networks—0
Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)—0
A stochastic metapopulation state-space approach to modeling and estimating Covid-19 spread—0
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data DetectionCode1
Cine-MRI detection of abdominal adhesions with spatio-temporal deep learning—0
Time Series Anomaly Detection for Cyber-Physical Systems via Neural System Identification and Bayesian FilteringCode1
The Economic Impact of Critical National Infrastructure Failure Due to Space Weather—0
EuroCrops: A Pan-European Dataset for Time Series Crop Type Classification—0
Next Generation Reservoir ComputingCode1
Hierarchically Regularized Deep Forecasting—0
A Two-Step Framework for Arbitrage-Free Prediction of the Implied Volatility Surface—0
Signal processing on simplicial complexes—0
A Self-Supervised Framework for Function Learning and Extrapolation—0
Dynamic Asymmetric Causality Tests with an Application—0
Differentiable Neural Architecture Search with Morphism-based Transformable Backbone Architectures—0
Graph Neural Network-Based Anomaly Detection in Multivariate Time SeriesCode1
Cross-Subject Domain Adaptation for Classifying Working Memory Load with Multi-Frame EEG Images—0
Geodesic Density Regression for Correcting 4DCT Pulmonary Respiratory Motion ArtifactsCode0
BRAIN2DEPTH: Lightweight CNN Model for Classification of Cognitive States from EEG Recordings—0
Semi-supervised Time Series Classification by Temporal Relation PredictionCode1
Multivariate Pair Trading by Volatility & Model Adaption Trade-off—0
Time Series Anomaly Detection with label-free Model Selection—0
Probability Paths and the Structure of Predictions over TimeCode0
Generative Adversarial Networks in finance: an overview—0
HIFI: Anomaly Detection for Multivariate Time Series with High-order Feature Interactions—0
WAX-ML: A Python library for machine learning and feedback loops on streaming dataCode1
Recurrent Trend Predictive Neural Network for Multi-Sensor Fire DetectionCode1
A new measure between sets of probability distributions with applications to erratic financial behavior—0
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties—0
Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random FeaturesCode0
RNN with Particle Flow for Probabilistic Spatio-temporal ForecastingCode1
Machine Learning Framework for Sensing and Modeling Interference in IoT Frequency Bands—0
Multistep Electric Vehicle Charging Station Occupancy Prediction using Hybrid LSTM Neural Networks—0
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series DataCode0
Towards Deep Industrial Transfer Learning for Anomaly Detection on Time Series Data—0
Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos—0
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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