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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4826–4850 of 6748 papers

TitleStatusHype
Quick, Stat!: A Statistical Analysis of the Quick, Draw! Dataset—0
An Artificial Spiking Quantum Neuron—0
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling—0
The Use of Gaussian Processes in System Identification—0
A machine learning framework for computationally expensive transient modelsCode0
Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks—0
Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence ModelCode0
General Evaluation for Instruction Conditioned Navigation using Dynamic Time WarpingCode1
Change point detection for graphical models in the presence of missing valuesCode0
Forecasting Time Series with VARMA Recursions on Graphs—0
Time series cluster kernels to exploit informative missingness and incomplete label information—0
Fetal Pose Estimation in Volumetric MRI using a 3D Convolution Neural Network—0
Kernel Hypothesis Testing with Set-valued Data—0
Using Temporal and Topological Features for Intrusion Detection in Operational Networks—0
GP-VAE: Deep Probabilistic Time Series ImputationCode0
Non-technical Loss Detection with Statistical Profile Images Based on Semi-supervised Learning—0
Routine Modeling with Time Series Metric Learning—0
Latent ODEs for Irregularly-Sampled Time SeriesCode1
Attending to Emotional NarrativesCode0
Fast ES-RNN: A GPU Implementation of the ES-RNN AlgorithmCode0
Takens-inspired neuromorphic processor: a downsizing tool for random recurrent neural networks via feature extraction—0
A Quantum Field Theory of Representation Learning—0
Financial Time Series Data Processing for Machine LearningCode1
VELC: A New Variational AutoEncoder Based Model for Time Series Anomaly DetectionCode0
Action Prediction in Humans and Robots—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