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

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Showing 4651–4700 of 6748 papers

TitleStatusHype
Large-Scale Characterization and Segmentation of Internet Path Delays with Infinite HMMsCode0
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural NetworksCode0
Deep Learning for Plasma Tomography and Disruption Prediction from Bolometer Data—0
Causal inference for climate change events from satellite image time series using computer vision and deep learning—0
Textual Data for Time Series Forecasting—0
Time Series Vector Autoregression Prediction of the Ecological Footprint based on Energy Parameters—0
High dimensional regression for regenerative time-series: an application to road traffic modelingCode0
Inference of Binary Regime Models with Jump Discontinuities—0
MLAT: Metric Learning for kNN in Streaming Time Series—0
Winning the ICCV 2019 Learning to Drive Challenge—0
Critical Transitions in Intensive Care Units: A Sepsis Case Study—0
Wasserstein total variation filtering—0
Self-attention for raw optical Satellite Time Series ClassificationCode0
Study of the impact of climate change on precipitation in Paris area using method based on iterative multiscale dynamic time warping (IMS-DTW)—0
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems—0
Generalised learning of time-series: Ornstein-Uhlenbeck processes—0
Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis—0
Order patterns, their variation and change points in financial time series and Brownian motion—0
Content Removal as a Moderation Strategy: Compliance and Other Outcomes in the ChangeMyView Community—0
You May Not Need Order in Time Series Forecasting—0
GesturePod: Enabling On-device Gesture-based Interaction for White Cane Users—0
Temporal Network Sampling—0
Coupling Oceanic Observation Systems to Study Mesoscale Ocean DynamicsCode0
Forecasting under Long Memory and Nonstationarity—0
Deep Amortized Variational Inference for Multivariate Time Series Imputation with Latent Gaussian Process Models—0
Automated Detection of Left Ventricle in Arterial Input Function Images for Inline Perfusion Mapping using Deep Learning: A study of 15,000 Patients—0
Variationally Inferred Sampling Through a Refined BoundCode0
Scalable Gradients and Variational Inference for Stochastic Differential Equations—0
A Single Scalable LSTM Model for Short-Term Forecasting of Disaggregated Electricity Loads—0
ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness—0
Jointly Discriminative and Generative Recurrent Neural Networks for Learning from fMRI—0
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainabilityCode0
Graph-based Knowledge Tracing: Modeling Student Proficiency Using Graph Neural NetworkCode0
Adaptive Transfer Learning of Multi-View Time Series Classification—0
Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems—0
Decoding Working Memory Load from EEG with LSTM Networks—0
Evolving Gaussian Process kernels from elementary mathematical expressions—0
Classification of Resting-State fMRI using Evolutionary Algorithms: Towards a Brain Imaging Biomarker for Parkinson's Disease—0
The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos?—0
Predicting dynamical system evolution with residual neural networks—0
Accelerometer-Based Gait Segmentation: Simultaneously User and Adversary Identification—0
On Computational Complexity Reduction Methods for Kalman Filter Extensions—0
Time series classification for varying length series—0
Graph Spectral Embedding for Parsimonious Transmission of Multivariate Time Series—0
Phase space reconstruction from a biological time series. A PhotoPlethysmoGraphic signal a case study—0
A Joint Model for IT Operation Series Prediction and Anomaly Detection—0
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth MeasureCode0
Continual Learning Using Bayesian Neural Networks—0
Probabilistic sequential matrix factorizationCode0
Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies—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