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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 141–150 of 6748 papers

Title	Date	Tasks	Status	Hype
SigKAN: Signature-Weighted Kolmogorov-Arnold Networks for Time Series	Jun 25, 2024	Kolmogorov-Arnold NetworksTime Series	CodeCode Available	1
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images	Jun 20, 2024	Decision MakingMedical Image Analysis	CodeCode Available	1
Time Series Representation Models	May 28, 2024	ImputationRepresentation Learning	CodeCode Available	1
Heracles: A Hybrid SSM-Transformer Model for High-Resolution Image and Time-Series Analysis	Mar 26, 2024	Inductive BiasInstance Segmentation	CodeCode Available	1
Self-Supervised Learning for Time Series: Contrastive or Generative?	Mar 14, 2024	Model OptimizationRepresentation Learning	CodeCode Available	1
MTSA-SNN: A Multi-modal Time Series Analysis Model Based on Spiking Neural Network	Feb 8, 2024	Time SeriesTime Series Analysis	CodeCode Available	1
PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly Detection	Jan 18, 2024	Anomaly DetectionContrastive Learning	CodeCode Available	1
DualDynamics: Synergizing Implicit and Explicit Methods for Robust Irregular Time Series Analysis	Jan 10, 2024	Irregular Time SeriesTime Series	CodeCode Available	1
Series2Vec: Similarity-based Self-supervised Representation Learning for Time Series Classification	Dec 7, 2023	Data AugmentationRepresentation Learning	CodeCode Available	1
Understanding the Role of Textual Prompts in LLM for Time Series Forecasting: an Adapter View	Nov 24, 2023	Anomaly DetectionFew-Shot Learning	CodeCode Available	1

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All datasets PhysioNet Challenge 2012 Speech Commands Ventilator Pressure Prediction

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	naive classifier	F1	87.47	—	Unverified
2	GRU-D - APC (n = 1)	F1	27.3	—	Unverified
3	GRU-APC (n = 1)	F1	25.7	—	Unverified
4	GRU-D	F1	22.5	—	Unverified
5	GRU	F1	22.3	—	Unverified
6	GRU-Simple	F1	22.2	—	Unverified
7	GRU-Mean	F1	22.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SepTr	% Test Accuracy	98.51	—	Unverified
2	ViT	% Test Accuracy	98.11	—	Unverified
3	FlexTCN-4	% Test Accuracy	97.73	—	Unverified
4	MatchboxNet	% Test Accuracy	97.4	—	Unverified
5	CKCNN (100k)	% Test Accuracy	95.27	—	Unverified
6	FlexTCN-6	% Test Accuracy (Raw Data)	91.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResBiLSTM	MAE	0.13	—	Unverified