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 16511675 of 6748 papers

TitleStatusHype
Accelerating Neural Architecture Search using Performance PredictionCode0
End-to-end learning of energy-based representations for irregularly-sampled signals and imagesCode0
Enhancing Time Series Momentum Strategies Using Deep Neural NetworksCode0
Probabilistic sequential matrix factorizationCode0
Elastic Product Quantization for Time SeriesCode0
Elastic Similarity and Distance Measures for Multivariate Time SeriesCode0
Causal Discovery with Attention-Based Convolutional Neural NetworksCode0
Causal Discovery using Model Invariance through Knockoff InterventionsCode0
Data Imputation for Multivariate Time Series Sensor Data with Large Gaps of Missing DataCode0
Elastic bands across the path: A new framework and methods to lower bound DTWCode0
E-LSTM-D: A Deep Learning Framework for Dynamic Network Link PredictionCode0
Efficient Matrix Profile Computation Using Different Distance FunctionsCode0
EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction with Exogenous VariablesCode0
Adaptive Anomaly Detection in Chaotic Time Series with a Spatially Aware Echo State NetworkCode0
Causal discovery for time series with latent confoundersCode0
Efficient learning of nonlinear prediction models with time-series privileged informationCode0
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantificationCode0
Enhancing Visual Inspection Capability of Multi-Modal Large Language Models on Medical Time Series with Supportive Conformalized and Interpretable Small Specialized ModelsCode0
Evaluating data augmentation for financial time series classificationCode0
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEsCode0
Generative Optimization Networks for Memory Efficient Data GenerationCode0
(Quasi)Periodicity Quantification in Video Data, Using TopologyCode0
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart CitiesCode0
Efficient Certified Training and Robustness Verification of Neural ODEsCode0
Edge computing on TPU for brain implant signal analysisCode0
Show:102550
← PrevPage 67 of 270Next →

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