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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 3101–3150 of 6748 papers

TitleStatusHype
Deep Reinforcement Learning for Portfolio Optimization using Latent Feature State Space (LFSS) Module—0
Testing Framework for Black-box AI Models—0
PatchX: Explaining Deep Models by Intelligible Pattern Patches for Time-series Classification—0
A Metamodel and Framework for Artificial General Intelligence From Theory to Practice—0
Comparative Analysis of Machine Learning Approaches to Analyze and Predict the Covid-19 Outbreak—0
Feature Selection for Multivariate Time Series via Network PruningCode0
Causal Inference for Time series Analysis: Problems, Methods and Evaluation—0
Anomaly Detection through Transfer Learning in Agriculture and Manufacturing IoT Systems—0
Systematic Generalization in Neural Networks-based Multivariate Time Series Forecasting ModelsCode0
Attentive Gaussian processes for probabilistic time-series generation—0
Self-supervised learning for fast and scalable time series hyper-parameter tuning—0
Inductive Granger Causal Modeling for Multivariate Time Series—0
Conditional Loss and Deep Euler Scheme for Time Series Generation—0
Concealer: SGX-based Secure, Volume Hiding, and Verifiable Processing of Spatial Time-Series Datasets—0
Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)—0
NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series ForecastingCode1
On Disentanglement in Gaussian Process Variational Autoencoders—0
Last Query Transformer RNN for knowledge tracingCode1
Early Abandoning and Pruning for Elastic Distances including Dynamic Time WarpingCode1
From sleep medicine to medicine during sleep: A clinical perspective—0
Bioluminescence modeling for deep sea experimentsCode0
Robust Optimization and Validation of Echo State Networks for learning chaotic dynamics—0
MALI: A memory efficient and reverse accurate integrator for Neural ODEsCode1
Meta-Learning for Koopman Spectral Analysis with Short Time-series—0
Reconstructing large networks with time-varying interactionsCode0
The Multi-Temporal Urban Development SpaceNet DatasetCode0
Plotting time: On the usage of CNNs for time series classification—0
Few-shot time series segmentation using prototype-defined infinite hidden Markov models—0
FedMood: Federated Learning on Mobile Health Data for Mood DetectionCode1
Deep Semi-Supervised Learning for Time Series ClassificationCode1
Neural SDEs as Infinite-Dimensional GANsCode2
Understanding the input-output relationship of neural networks in the time series forecasting radon levels at Canfranc Underground Laboratory—0
NRTSI: Non-Recurrent Time Series ImputationCode1
Exploring asymmetric multifractal cross-correlations of price-volatility and asymmetric volatility dynamics in cryptocurrency markets—0
Forecasting Using Reservoir Computing: The Role of Generalized Synchronization—0
Nonlinear Independent Component Analysis for Discrete-Time and Continuous-Time SignalsCode0
CKConv: Continuous Kernel Convolution For Sequential DataCode1
Long time-series NDVI reconstruction in cloud-prone regions via spatio-temporal tensor completion—0
Deep Hedging under Rough Volatility—0
AttentionFlow: Visualising Influence in Networks of Time Series—0
Uncertain Time Series Classification With Shapelet TransformCode1
Time Series Classification via Topological Data Analysis—0
Policy Analysis using Synthetic Controls in Continuous-TimeCode0
A Stochastic Time Series Model for Predicting Financial Trends using NLP—0
Time Adaptive Gaussian Model—0
Anomaly Detection of Time Series with Smoothness-Inducing Sequential Variational Auto-Encoder—0
Impulse data models for the inverse problem of electrocardiography—0
Stochastic Online Convex Optimization. Application to probabilistic time series forecasting—0
Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning—0
A Novel Approach for Classification and Forecasting of Time Series in Particle Accelerators—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