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 2901–2950 of 6748 papers

TitleStatusHype
Generating Student Feedback from Time-Series Data Using Reinforcement Learning—0
Generating Trading Signals by ML algorithms or time series ones?—0
Generation of a Supervised Classification Algorithm for Time-Series Variable Stars with an Application to the LINEAR Dataset—0
Generation of Synthetic Multi-Resolution Time Series Load Data—0
Generative adversarial network based on chaotic time series—0
Construction of neural networks for realization of localized deep learning—0
A Novel Hybrid Framework for Hourly PM2.5 Concentration Forecasting Using CEEMDAN and Deep Temporal Convolutional Neural Network—0
Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination—0
Generative Adversarial Networks for Spatio-temporal Data: A Survey—0
Generative Adversarial Networks in finance: an overview—0
Bayesian Neural Networks for Macroeconomic Analysis—0
Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning—0
Generative Modeling of Hidden Functional Brain Networks—0
Generative modeling of spatio-temporal weather patterns with extreme event conditioning—0
Causal Inference in Non-linear Time-series using Deep Networks and Knockoff Counterfactuals—0
Content Removal as a Moderation Strategy: Compliance and Other Outcomes in the ChangeMyView Community—0
Generative Pre-Trained Transformer for Cardiac Abnormality Detection—0
Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks—0
Generative Time-series Modeling with Fourier Flows—0
Energy time series forecasting-Analytical and empirical assessment of conventional and machine learning models—0
Gene Regulatory Network Inference with Latent Force Models—0
Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving—0
Generic Variance Bounds on Estimation and Prediction Errors in Time Series Analysis: An Entropy Perspective—0
A Signal Detection Scheme Based on Deep Learning in OFDM Systems—0
Geodesic Properties of a Generalized Wasserstein Embedding for Time Series Analysis—0
Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds—0
GEOMETRIC AUGMENTATION FOR ROBUST NEURAL NETWORK CLASSIFIERS—0
Geometric feature performance under downsampling for EEG classification tasks—0
Geometric Fusion via Joint Delay Embeddings—0
Geometric Optimisation on Manifolds with Applications to Deep Learning—0
Geospatial and Temporal Trends in Urban Transportation: A Study of NYC Taxis and Pathao Food Deliveries—0
GesturePod: Enabling On-device Gesture-based Interaction for White Cane Users—0
Gesture Recognition from Skeleton Data for Intuitive Human-Machine Interaction—0
A cloud-IoT platform for passive radio sensing: challenges and application case studies—0
Gesture Recognition in Robotic Surgery: a Review—0
GG-SSMs: Graph-Generating State Space Models—0
Global Constraint Catalog, Volume II, Time-Series Constraints—0
Global Flood Prediction: a Multimodal Machine Learning Approach—0
Continual Learning Using Bayesian Neural Networks—0
Causal Inference for Time series Analysis: Problems, Methods and Evaluation—0
A novel health risk model based on intraday physical activity time series collected by smartphones—0
A High GOPs/Slice Time Series Classifier for Portable and Embedded Biomedical Applications—0
Energy Predictive Models with Limited Data using Transfer Learning—0
Go with the FLOW: Visualizing spatiotemporal dynamics in optical widefield calcium imaging—0
GP Kernels for Cross-Spectrum Analysis—0
Energy-Efficient Seizure Detection Suitable for low-power Applications—0
GPRInvNet: Deep Learning-Based Ground Penetrating Radar Data Inversion for Tunnel Lining—0
GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model—0
A Single Scalable LSTM Model for Short-Term Forecasting of Disaggregated Electricity Loads—0
Causal inference for climate change events from satellite image time series using computer vision and deep learning—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