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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3101–3125 of 6748 papers

TitleStatusHype
Short-Term Stock Price-Trend Prediction Using Meta-Learning—0
Accelerating Neural ODEs Using Model Order Reduction—0
High Tension Lines: Predicting robustness of high-voltage power-grids to cascading failure using network embedding—0
Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network—0
Recurrent-type Neural Networks for Real-time Short-term Prediction of Ship Motions in High Sea State—0
Operator Autoencoders: Learning Physical Operations on Encoded Molecular Graphs—0
Anomaly Detection in Predictive Maintenance: A New Evaluation Framework for Temporal Unsupervised Anomaly Detection Algorithms—0
Three Remarks On Asset Pricing—0
Inferring Temporal Logic Properties from Data using Boosted Decision Trees—0
Matched Illumination Waveforms using Multi-Tone Sinusoidal Frequency Modulation—0
Can we imitate the principal investor's behavior to learn option price?—0
Financial Time Series Analysis and Forecasting with HHT Feature Generation and Machine Learning—0
Post-Radiotherapy PET Image Outcome Prediction by Deep Learning under Biological Model Guidance: A Feasibility Study of Oropharyngeal Cancer Application—0
Photonic neural field on a silicon chip: large-scale, high-speed neuro-inspired computing and sensing—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
RFID-based Article-to-Fixture Predictions in Real-World Fashion Stores—0
Entropy-based Discovery of Summary Causal Graphs in Time Series—0
Quantifying Topology In Pancreatic Tubular Networks From Live Imaging 3D Microscopy—0
Fixed-k Tail Regression: New Evidence on Tax and Wealth Inequality from Forbes 400—0
Monte Carlo Filtering Objectives: A New Family of Variational Objectives to Learn Generative Model and Neural Adaptive Proposal for Time Series—0
Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly DetectionCode0
Periodic Freight Demand Estimation for Large-scale Tactical Planning—0
Learning Representations for Incomplete Time Series Clustering—0
Univariate Long-Term Municipal Water Demand Forecasting—0
ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework for Human Activity RecognitionCode0
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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