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 721–730 of 6748 papers

Title	Date	Tasks	Status	Hype
A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vessels	Jul 12, 2022	Action DetectionActivity Detection	CodeCode Available	1
A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learning	Apr 2, 2022	Crop ClassificationSemantic Segmentation	CodeCode Available	1
MAD: Self-Supervised Masked Anomaly Detection Task for Multivariate Time Series	May 4, 2022	Anomaly DetectionSelf-Supervised Learning	CodeCode Available	1
MAGIC: Microlensing Analysis Guided by Intelligent Computation	Jun 16, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	Sep 9, 2019	Object LocalizationPrediction	CodeCode Available	1
Manifold Topology Divergence: a Framework for Comparing Data Manifolds	Jun 8, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection	Jul 25, 2022	Anomaly DetectionOne-Class Classification	CodeCode Available	1
Massively Parallel Causal Inference of Whole Brain Dynamics at Single Neuron Resolution	Dec 2, 2020	Causal InferenceGPU	CodeCode Available	1
Can Multimodal LLMs Perform Time Series Anomaly Detection?	Feb 25, 2025	Anomaly DetectionIrregular Time Series	CodeCode Available	1
Bilinear Input Normalization for Neural Networks in Financial Forecasting	Sep 1, 2021	Time SeriesTime Series Analysis	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