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 1101–1150 of 6748 papers

TitleStatusHype
Transfer Learning-based State of Health Estimation for Lithium-ion Battery with Cycle Synchronization—0
Ordinal analysis of lexical patterns—0
We Are in This Together: Quantifying Community Subjective Wellbeing and Resilience—0
Multimodal Crop Type Classification Fusing Multi-Spectral Satellite Time Series with Farmers Crop Rotations and Local Crop Distribution—0
Inter- and Intra-Series Embeddings Fusion Network for Epidemiological ForecastingCode0
Prediction of good reaction coordinates and future evolution of MD trajectories using Regularized Sparse Autoencoders: A novel deep learning approach—0
ArNet-ECG: Deep Learning for the Detection of Atrial Fibrillation from the Raw Electrocardiogram—0
Predicting the Biological Classification of Cell-Cycle Regulated Genes of Saccharomyces cerevisiae using Community Detection Algorithms on Gene Co-expression Networks—0
Towards an AI-based Early Warning System for Bridge Scour—0
Shapelet-Based Counterfactual Explanations for Multivariate Time SeriesCode0
Stop&Hop: Early Classification of Irregular Time SeriesCode1
AA-Forecast: Anomaly-Aware Forecast for Extreme EventsCode1
From Time Series to Networks in R with the ts2net PackageCode1
A decomposition of book structure through ousiometric fluctuations in cumulative word-time—0
Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series DataCode1
Expressing Multivariate Time Series as Graphs with Time Series Attention TransformerCode1
Diffusion-based Time Series Imputation and Forecasting with Structured State Space ModelsCode2
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders PredictionCode0
Efficient data-driven gap filling of satellite image time series using deep neural networks with partial convolutionsCode1
Learning-based estimation of in-situ wind speed from underwater acoustics—0
Network inference via process motifs for lagged correlation in linear stochastic processes—0
KDD CUP 2022 Wind Power Forecasting Team 88VIP Solution—0
Sequence Prediction Under Missing Data : An RNN Approach Without Imputation—0
NeurIPS Competition Instructions and Guide: Causal Insights for Learning Paths in Education—0
Progressive Cross-modal Knowledge Distillation for Human Action Recognition—0
Time is limited on the road to asymptopia—0
The Counterfactual-Shapley Value: Attributing Change in System Metrics—0
Expressivity of Hidden Markov Chains vs. Recurrent Neural Networks from a system theoretic viewpoint—0
Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock Market—0
ODformer: Spatial-Temporal Transformers for Long Sequence Origin-Destination Matrix Forecasting Against Cross Application Scenario—0
Neural Networks for Extreme Quantile Regression with an Application to Forecasting of Flood RiskCode1
Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives—0
Grasping Core Rules of Time Series through Pure Models—0
Confidence-Guided Learning Process for Continuous Classification of Time Series—0
Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series ClassificationCode2
An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain InjuryCode0
Feature-Based Time-Series Analysis in R using the theft PackageCode1
Towards Coupling Full-disk and Active Region-based Flare Prediction for Operational Space Weather ForecastingCode0
Real-Time Massive MIMO Channel Prediction: A Combination of Deep Learning and NeuralProphet—0
Uncertainty Quantification for Traffic Forecasting: A Unified Approach—0
Approximate Extraction of Late-Time Returns via Morphological Component Analysis—0
HyperTime: Implicit Neural Representation for Time Series—0
Quantification of metabolic niche occupancy dynamics in a Baltic Sea bacterial community—0
Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series ForecastingCode2
Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy—0
TSInterpret: A unified framework for time series interpretabilityCode1
Estimating Sunlight Using GNSS Signal Strength from Smartphone—0
Representation learning of rare temporal conditions for travel time prediction—0
Liquid State Machine-Empowered Reflection Tracking in RIS-Aided THz Communications—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