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 401450 of 6748 papers

TitleStatusHype
RePAD2: Real-Time, Lightweight, and Adaptive Anomaly Detection for Open-Ended Time Series0
Edge computing on TPU for brain implant signal analysisCode0
Interpretable Water Level Forecaster with Spatiotemporal Causal Attention Mechanisms0
Learning Hidden Markov Models Using Conditional Samples0
Your time series is worth a binary image: machine vision assisted deep framework for time series forecastingCode0
Time Series Anomaly Detection in Smart Homes: A Deep Learning Approach0
Stock Broad-Index Trend Patterns Learning via Domain Knowledge Informed Generative NetworkCode1
Nickell Bias in Panel Local Projection: Financial Crises Are Worse Than You ThinkCode0
A Tale of Tail Covariances (and Diversified Tails)0
Combating Uncertainties in Wind and Distributed PV Energy Sources Using Integrated Reinforcement Learning and Time-Series Forecasting0
A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to TBI Phenotyping0
Deep Imbalanced Time-series Forecasting via Local Discrepancy DensityCode0
A Synthetic Texas Power System with Time-Series Weather-Dependent Spatiotemporal ProfilesCode1
Robust language-based mental health assessments in time and space through social media0
In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance0
Chaotic Variational Auto encoder-based Adversarial Machine Learning0
Detecting Rough Volatility: A Filtering Approach0
LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation -- Extended VersionCode1
Statistical Inference with Stochastic Gradient Methods under φ-mixing Data0
T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease ProgressionCode0
Set Features for Fine-grained Anomaly DetectionCode1
One Fits All:Power General Time Series Analysis by Pretrained LMCode2
A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers0
A metric to compare the anatomy variation between image time series0
Adaptive Sampling for Probabilistic Forecasting under Distribution Shift0
Generalization of Auto-Regressive Hidden Markov Models to Non-Linear Dynamics and Unit Quaternion Observation Space0
LightCTS: A Lightweight Framework for Correlated Time Series ForecastingCode1
Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference0
Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series ForecastingCode1
Time-varying Signals Recovery via Graph Neural Networks0
Information Theory Inspired Pattern Analysis for Time-series Data0
Learning Mixture Structure on Multi-Source Time Series for Probabilistic Forecasting0
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles0
The DeepCAR Method: Forecasting Time-Series Data That Have Change PointsCode0
Measuring city-scale green infrastructure drawdown dynamics using internet-connected sensors in Detroit0
MVMTnet: A Multi-variate Multi-modal Transformer for Multi-class Classification of Cardiac Irregularities Using ECG Waveforms and Clinical NotesCode1
Enhancing Energy System Models Using Better Load Forecasts0
Task-Oriented Prediction and Communication Co-Design for Haptic Communications0
TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts0
Creating Disasters: Recession Forecasting with GAN-Generated Synthetic Time Series Data0
Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather StationsCode1
FedST: Secure Federated Shapelet Transformation for Time Series Classification0
Exploring the Advantages of Transformers for High-Frequency TradingCode1
Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional StrategiesCode1
Online Evolutionary Neural Architecture Search for Multivariate Non-Stationary Time Series Forecasting0
Toward Asymptotic Optimality: Sequential Unsupervised Regression of Density Ratio for Early ClassificationCode0
FormerTime: Hierarchical Multi-Scale Representations for Multivariate Time Series Classification0
CNTS: Cooperative Network for Time SeriesCode0
Dynamic Graph Neural Network with Adaptive Edge Attributes for Air Quality Predictions0
Ergodic characterization of non-ergodic anomalous diffusion processes0
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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