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 526–550 of 6748 papers

TitleStatusHype
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty QuantificationCode1
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution TestsCode1
Integrating LSTMs and GNNs for COVID-19 ForecastingCode1
Deep Autoregressive Models with Spectral AttentionCode1
Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and ResultsCode1
Short-term Renewable Energy Forecasting in Greece using Prophet Decomposition and Tree-based EnsemblesCode1
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic HardwareCode1
Measuring Financial Time Series Similarity With a View to Identifying Profitable Stock Market OpportunitiesCode1
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series ImputationCode1
Keiki: Towards Realistic Danmaku Generation via Sequential GANsCode1
Spatiotemporal information conversion machine for time-series predictionCode1
Online Metro Origin-Destination Prediction via Heterogeneous Information AggregationCode1
Market regime classification with signaturesCode1
Continuous Latent Process FlowsCode1
Time-Series Representation Learning via Temporal and Contextual ContrastingCode1
Automated Evolutionary Approach for the Design of Composite Machine Learning PipelinesCode1
Accelerating Recurrent Neural Networks for Gravitational Wave ExperimentsCode1
Continuous-Time Deep Glioma Growth ModelsCode1
Spatio-Temporal SAR-Optical Data Fusion for Cloud Removal via a Deep Hierarchical ModelCode1
Unsupervised Speech Enhancement using Dynamical Variational Auto-EncodersCode1
STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised LearningCode1
Neural Controlled Differential Equations for Online Prediction TasksCode1
GPLA-12: An Acoustic Signal Dataset of Gas Pipeline LeakageCode1
TS2Vec: Towards Universal Representation of Time SeriesCode1
FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable StocksCode1
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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