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 151–200 of 477 papers

TitleStatusHype
Characterizing Learning in Spiking Neural Networks with Astrocyte-Like Units—0
A Self-organizing Interval Type-2 Fuzzy Neural Network for Multi-Step Time Series Prediction—0
Impact of noise on a dynamical system: prediction and uncertainties from a swarm-optimized neural network—0
Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks—0
Evaluating Preprocessing Strategies for Time Series Prediction Using Deep Learning Architectures—0
CGS-Mask: Making Time Series Predictions Intuitive for All—0
Enhancing Mean-Reverting Time Series Prediction with Gaussian Processes: Functional and Augmented Data Structures in Financial Forecasting—0
Can Competition Enhance the Proficiency of Agents Powered by Large Language Models in the Realm of News-driven Time Series Forecasting?—0
Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning—0
Hybridization of Persistent Homology with Neural Networks for Time-Series Prediction: A Case Study in Wave Height—0
Hypercomplex neural network in time series forecasting of stock data—0
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization—0
Imposing Connectome-Derived Topology on an Echo State Network—0
Ensemble quantile-based deep learning framework for streamflow and flood prediction in Australian catchments—0
Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models—0
Event prediction and causality inference despite incomplete information—0
Evolutionary Ensemble Learning for Multivariate Time Series Prediction—0
Excess risk bound for deep learning under weak dependence—0
Efficient Online Learning with Memory via Frank-Wolfe Optimization: Algorithms with Bounded Dynamic Regret and Applications to Control—0
Experimental demonstration of bandwidth enhancement in photonic time delay reservoir computing—0
Efficient Online Hyperparameter Optimization for Kernel Ridge Regression with Applications to Traffic Time Series Prediction—0
Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop—0
A Comparative Study of Reservoir Computing for Temporal Signal Processing—0
Explainable Time Series Prediction of Tyre Energy in Formula One Race Strategy—0
Efficient Interpretable Nonlinear Modeling for Multiple Time Series—0
Effects of cavity nonlinearities and linear losses on silicon microring-based reservoir computing—0
Bridging the Modality Gap: Enhancing Channel Prediction with Semantically Aligned LLMs and Knowledge Distillation—0
Hidformer: Transformer-Style Neural Network in Stock Price Forecasting—0
Extreme-Long-short Term Memory for Time-series Prediction—0
Fast Function to Function Regression—0
Feature-Based Echo-State Networks: A Step Towards Interpretability and Minimalism in Reservoir Computer—0
Effect of temporal resolution on the reproduction of chaotic dynamics via reservoir computing—0
An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution—0
Financial series prediction using Attention LSTM—0
Multi-task Photonic Reservoir Computing: Wavelength Division Multiplexing for Parallel Computing with a Silicon Microring Resonator—0
FinTSBridge: A New Evaluation Suite for Real-world Financial Prediction with Advanced Time Series Models—0
Comparison of Traditional and Hybrid Time Series Models for Forecasting COVID-19 Cases—0
Forecasting Photovoltaic Power Production using a Deep Learning Sequence to Sequence Model with Attention—0
Forecasting steam mass flow in power plants using the parallel hybrid network—0
Fourier-RNNs for Modelling Noisy Physics Data—0
Conditional Risk Minimization for Stochastic Processes—0
EAMDrift: An interpretable self retrain model for time series—0
EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction—0
Finite volume method network for acceleration of unsteady computational fluid dynamics: non-reacting and reacting flows—0
Brain-Inspired Spiking Neural Network for Online Unsupervised Time Series Prediction—0
GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets—0
Generalized Mixture Model for Extreme Events Forecasting in Time Series Data—0
Constraints on parameter choices for successful reservoir computing—0
Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving—0
Hidden Markov Model: Tutorial—0
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Benchmark Results

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