SOTAVerified

Time Series Prediction

The goal of Time Series Prediction is to infer the future values of a time series from the past.

Source: Orthogonal Echo State Networks and stochastic evaluations of likelihoods

Papers

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Showing 1–50 of 477 papers

TitleStatusHype
GluonTS: Probabilistic Time Series Models in PythonCode3
Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price PredictionCode2
PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series ForecastingCode2
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning ProcessCode2
Trainable Fractional Fourier TransformCode2
UnetTSF: A Better Performance Linear Complexity Time Series Prediction ModelCode2
PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow PredictionCode2
An Extensive Data Processing Pipeline for MIMIC-IVCode2
LibCity: An Open Library for Traffic PredictionCode2
Closed-form Continuous-time Neural ModelsCode2
Liquid Time-constant NetworksCode2
Deep Learning for Time Series Forecasting: Tutorial and Literature SurveyCode2
Bayesian Temporal Factorization for Multidimensional Time Series PredictionCode2
IMTS is Worth Time Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series PredictionCode1
CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial CorrelationsCode1
Error-quantified Conformal Inference for Time SeriesCode1
SWIFT: Mapping Sub-series with Wavelet Decomposition Improves Time Series ForecastingCode1
PowerMamba: A Deep State Space Model and Comprehensive Benchmark for Time Series Prediction in Electric Power SystemsCode1
Recursive Gaussian Process State Space ModelCode1
An Evaluation of Deep Learning Models for Stock Market Trend PredictionCode1
SIGMA: Selective Gated Mamba for Sequential RecommendationCode1
CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series ForecastingCode1
Leveraging 2D Information for Long-term Time Series Forecasting with Vanilla TransformersCode1
Time Series Forecasting with LLMs: Understanding and Enhancing Model CapabilitiesCode1
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process Download PDFCode1
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series PredictionCode1
How Does It Function? Characterizing Long-term Trends in Production Serverless WorkloadsCode1
Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series ForecastingCode1
Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural NetworksCode1
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time SeriesCode1
MemDA: Forecasting Urban Time Series with Memory-based Drift AdaptationCode1
Transformers versus LSTMs for electronic tradingCode1
Conformal PID Control for Time Series PredictionCode1
MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series PredictionCode1
Feature Programming for Multivariate Time Series PredictionCode1
One for All: Unified Workload Prediction for Dynamic Multi-tenant Edge Cloud PlatformsCode1
Temporal and Heterogeneous Graph Neural Network for Financial Time Series PredictionCode1
Multi-step-ahead Stock Price Prediction Using Recurrent Fuzzy Neural Network and Variational Mode DecompositionCode1
Temporal Saliency Detection Towards Explainable Transformer-based Timeseries ForecastingCode1
An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural NetworksCode1
AA-Forecast: Anomaly-Aware Forecast for Extreme EventsCode1
MFRFNN: Multi-Functional Recurrent Fuzzy Neural Network for Chaotic Time Series PredictionCode1
TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study)Code1
Sparse Graph Learning from Spatiotemporal Time SeriesCode1
A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19Code1
Structured Time Series Prediction without Structural PriorCode1
Financial time series forecasting with multi-modality graph neural networkCode1
Neural network stochastic differential equation models with applications to financial data forecastingCode1
Non-Gaussian Gaussian Processes for Few-Shot RegressionCode1
Second-Order Neural ODE OptimizerCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CMU-DEMAverage mean absolute error9.06—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMRMSE0—Unverified