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 3701–3750 of 6748 papers

TitleStatusHype
SuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems—0
Predicting the Future is like Completing a Painting!—0
Predicting Landsat Reflectance with Deep Generative FusionCode0
ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data AnalysisCode0
The quantization error in a Self-Organizing Map as a contrast and colour specific indicator of single-pixel change in large random patterns—0
Gaussian Processes with Skewed Laplace Spectral Mixture Kernels for Long-term Forecasting—0
Deep Learning Alternative to Explicit Model Predictive Control for Unknown Nonlinear Systems—0
Robust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Models—0
Merchant Category Identification Using Credit Card Transactions—0
Predictive Process Model Monitoring using Recurrent Neural Networks—0
Statistical analysis of Wasserstein GANs with applications to time series forecasting—0
Applying Machine Learning to Crowd-sourced Data from Earthquake DetectiveCode0
A Tree-structure Convolutional Neural Network for Temporal Features Exaction on Sensor-based Multi-resident Activity Recognition—0
S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation—0
GAGE: Geometry Preserving Attributed Graph Embeddings—0
Time Series Forecasting with Stacked Long Short-Term Memory Networks—0
Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model—0
I miss you babe: Analyzing Emotion Dynamics During COVID-19 Pandemic—0
A Lane-Changing Prediction Method Based on Temporal Convolution Network—0
ORBITS: Online Recovery of Missing Blocks in Multiple Time Series StreamsCode0
Structured Self-AttentionWeights Encode Semantics in Sentiment AnalysisCode0
Creating cloud-free satellite imagery from image time series with deep learning—0
Modern strategies for time series regression—0
Multiscale characteristics of the emerging global cryptocurrency market—0
Machine Learning Link Inference of Noisy Delay-coupled Networks with Opto-Electronic Experimental Tests—0
Self-awareness in intelligent vehicles: Feature based dynamic Bayesian models for abnormality detection—0
Evaluating data augmentation for financial time series classificationCode0
Collective Awareness for Abnormality Detection in Connected Autonomous Vehicles—0
Augmenting transferred representations for stock classification—0
Hybrid Backpropagation Parallel Reservoir Networks—0
Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent KernelsCode0
Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks—0
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting—0
Smart Anomaly Detection in Sensor Systems: A Multi-Perspective Review—0
An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems—0
A Systematic Comparison of Forecasting for Gross Domestic Product in an Emergent Economy—0
Quasi-steady uptake and bacterial community assembly in a mathematical model of soil-phosphorus mobility—0
Peak Detection On Data Independent Acquisition Mass Spectrometry Data With Semisupervised Convolutional Transformers—0
Estimation of the mortality rate functions from time series field data in a stage-structured demographic model for Lobesia botrana—0
Blind Deinterleaving of Signals in Time Series with Self-attention Based Soft Min-cost Flow Learning—0
Towards Safe Policy Improvement for Non-Stationary MDPsCode0
Loss-analysis via Attention-scale for Physiologic Time Series—0
Model of continuous random cascade processes in financial markets—0
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health EpisodesCode0
CellCycleGAN: Spatiotemporal Microscopy Image Synthesis of Cell Populations using Statistical Shape Models and Conditional GANs—0
A novel convolutional neural network model to remove muscle artifacts from EEG—0
Prediction of Rainfall in Rajasthan, India using Deep and Wide Neural Network—0
Comparison of ARIMA, ETS, NNAR and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy—0
VenoMave: Targeted Poisoning Against Speech RecognitionCode0
A study of the Multicriteria decision analysis based on the time-series features and a TOPSIS method proposal for a tensorial approach—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