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 1951–2000 of 6748 papers

TitleStatusHype
On the Parameterization and Initialization of Diagonal State Space Models—0
Statistical inference of lead-lag at various timescales between asynchronous time series from p-values of transfer entropy—0
A Transfer-Learning Based Ensemble Architecture for ECG Signal Classification—0
Twitter conversations predict the daily confirmed COVID-19 casesCode0
ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces—0
Guiding Visual Attention in Deep Convolutional Neural Networks Based on Human Eye Movements—0
DisCoVQA: Temporal Distortion-Content Transformers for Video Quality AssessmentCode0
Time Gated Convolutional Neural Networks for Crop Classification—0
Understanding the Role of Weather Data for Earth Surface Forecasting using a ConvLSTM-based ModelCode0
An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation—0
Traffic-Twitter Transformer: A Nature Language Processing-joined Framework For Network-wide Traffic Forecasting—0
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift—0
Autoencoding Conditional GAN for Portfolio Allocation Diversification—0
User Engagement in Mobile Health Applications—0
Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings—0
Cyclocopula Technique to Study the Relationship Between Two Cyclostationary Time Series with Fractional Brownian Motion Errors—0
Learning with little mixing—0
Domain Generalization via Selective Consistency Regularization for Time Series Classification—0
Evaluating Short-Term Forecasting of Multiple Time Series in IoT EnvironmentsCode0
Calibrating Agent-based Models to Microdata with Graph Neural Networks—0
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning—0
Improving Solar Flare Prediction by Time Series Outlier Detection—0
Safe-FinRL: A Low Bias and Variance Deep Reinforcement Learning Implementation for High-Freq Stock Trading—0
Robust Time Series Denoising with Learnable Wavelet Packet Transform—0
Using generalized additive models to decompose time series and waveforms, and dissect heart-lung interaction physiologyCode0
Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets—0
DRAformer: Differentially Reconstructed Attention Transformer for Time-Series Forecasting—0
ProActive: Self-Attentive Temporal Point Process Flows for Activity SequencesCode0
Beyond the Gates of Euclidean Space: Temporal-Discrimination-Fusions and Attention-based Graph Neural Network for Human Activity Recognition—0
Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review—0
It's a super deal -- train recurrent network on noisy data and get smooth prediction free—0
Exploring Predictive States via Cantor Embeddings and Wasserstein Distance—0
Fault Diagnosis of Inter-turn Short Circuit in Permanent Magnet Synchronous Motors with Current Signal Imaging and Unsupervised Learning—0
Multivariate backtests and copulas for risk evaluation—0
Smart Meter Data Anomaly Detection using Variational Recurrent Autoencoders with Attention—0
Classification of Stochastic Processes with Topological Data Analysis—0
Spatial-Temporal Adaptive Graph Convolution with Attention Network for Traffic Forecasting—0
Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection—0
On the balance between the training time and interpretability of neural ODE for time series modelling—0
Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data—0
Forecasting COVID- 19 cases using Statistical Models and Ontology-based Semantic Modelling: A real time data analytics approach—0
DDPG based on multi-scale strokes for financial time series trading strategy—0
Using Connectome Features to Constrain Echo State Networks—0
Causal impact of severe events on electricity demand: The case of COVID-19 in Japan—0
Forecasting the production of Distillate Fuel Oil Refinery and Propane Blender net production by using Time Series Algorithms—0
Geodesic Properties of a Generalized Wasserstein Embedding for Time Series Analysis—0
Human Activity Recognition on Time Series Accelerometer Sensor Data using LSTM Recurrent Neural Networks—0
Constraints on parameter choices for successful reservoir computing—0
Generating Sparse Counterfactual Explanations For Multivariate Time SeriesCode0
Learning code summarization from a small and local dataset—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