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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 101–125 of 6748 papers

TitleStatusHype
Machine Learning Algorithms to Assess Site Closure Time Frames for Soil and Groundwater ContaminationCode0
Multiscale Dubuc: A New Similarity Measure for Time SeriesCode0
Sparse Interval-valued Time Series Modeling with Machine Learning—0
How to quantify interaction strengths? A critical rethinking of the interaction Jacobian and evaluation methods for non-parametric inference in time series analysis—0
Peri-midFormer: Periodic Pyramid Transformer for Time Series AnalysisCode1
Towards Resource-Efficient Federated Learning in Industrial IoT for Multivariate Time Series Analysis—0
Upcycling Human Excrement: The Gut Microbiome to Soil Microbiome Axis—0
bursty_dynamics: A Python Package for Exploring the Temporal Properties of Longitudinal Data—0
Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis—0
Enhancing Glucose Level Prediction of ICU Patients through Hierarchical Modeling of Irregular Time-SeriesCode0
Abstracted Shapes as Tokens -- A Generalizable and Interpretable Model for Time-series ClassificationCode1
Gradient-free training of recurrent neural networksCode0
Higher-order Cross-structural Embedding Model for Time Series Analysis—0
A Systematic Literature Review of Spatio-Temporal Graph Neural Network Models for Time Series Forecasting and Classification—0
Reconstructing dynamics from sparse observations with no training on target systemCode1
Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification—0
QIXAI: A Quantum-Inspired Framework for Enhancing Classical and Quantum Model Transparency and Understanding—0
TimeMixer++: A General Time Series Pattern Machine for Universal Predictive AnalysisCode5
HiPPO-KAN: Efficient KAN Model for Time Series Analysis—0
On the Regularization of Learnable Embeddings for Time Series Processing—0
Irregularity-Informed Time Series Analysis: Adaptive Modelling of Spatial and Temporal DynamicsCode0
Revisited Large Language Model for Time Series Analysis through Modality Alignment—0
SensorLLM: Human-Intuitive Alignment of Multivariate Sensor Data with LLMs for Activity RecognitionCode2
Building a Multivariate Time Series Benchmarking Datasets Inspired by Natural Language Processing (NLP)—0
Graph Neural Alchemist: An innovative fully modular architecture for time series-to-graph classification—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