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 91–100 of 6748 papers

Title	Date	Tasks	Status	Hype	Score
ETSformer: Exponential Smoothing Transformers for Time-series Forecasting	Feb 3, 2022	Time SeriesTime Series Analysis	CodeCode Available	2	5
Domino: Discovering Systematic Errors with Cross-Modal Embeddings	Mar 24, 2022	Representation LearningSlice Discovery	CodeCode Available	2	5
Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning	Feb 7, 2024	Contrastive LearningPrediction	CodeCode Available	2	5
AR-Net: A simple Auto-Regressive Neural Network for time-series	Nov 27, 2019	Time SeriesTime Series Analysis	CodeCode Available	2	5
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models	Aug 19, 2022	ImputationMissing Values	CodeCode Available	2	5
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting	Jan 30, 2022	Time SeriesTime Series Analysis	CodeCode Available	2	5
N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting	Jan 30, 2022	Time SeriesTime Series Analysis	CodeCode Available	2	5
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks	Apr 13, 2017	Multivariate Time Series ForecastingProbabilistic Time Series Forecasting	CodeCode Available	2	5
Deep learning for time series classification: a review	Sep 12, 2018	Deep LearningGeneral Classification	CodeCode Available	2	5
CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting	Feb 3, 2022	Contrastive LearningRepresentation Learning	CodeCode Available	2	5

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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