Time Series Regression
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Benchmarks
Most implemented
A Transformer-based Framework for Multivariate Time Series Representation Learning
A Multi-Horizon Quantile Recurrent Forecaster
Robustness Verification of Deep Neural Networks using Star-Based Reachability Analysis with Variable-Length Time Series Input
Changepoint Detection in Noisy Data Using a Novel Residuals Permutation-Based Method (RESPERM): Benchmarking and Application to Single Trial ERPs
Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection
Monash University, UEA, UCR Time Series Extrinsic Regression Archive
Papers
CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning
Accurately quantifying terrestrial carbon exchange is essential for climate policy and carbon accounting, yet models must generalize to ecosystems underrepresented in sparse eddy covariance observations. Despite this cha…
Time Series RegressionZero-Shot LearningTransfer LearningHarmonica: A Self-Adaptation Exemplar for Sustainable MLOps
Machine learning enabled systems (MLS) often operate in settings where they regularly encounter uncertainties arising from changes in their surrounding environment. Without structured oversight, such changes can degrade …
Time Series RegressionTS-HINT: Enhancing Semiconductor Time Series Regression Using Attention Hints From Large Language Model Reasoning
Existing data-driven methods rely on the extraction of static features from time series to approximate the material removal rate (MRR) of semiconductor manufacturing processes such as chemical mechanical polishing (CMP).…
Time Series RegressionFew-Shot LearningWhen, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate
Time series extrinsic regression (TSER) refers to the task of predicting a continuous target variable from an input time series. It appears in many domains, including healthcare, finance, environmental monitoring, and en…
Time Series RegressionFIC-TSC: Learning Time Series Classification with Fisher Information Constraint
Analyzing time series data is crucial to a wide spectrum of applications, including economics, online marketplaces, and human healthcare. In particular, time series classification plays an indispensable role in segmentin…
ClassificationTime SeriesTime Series ClassificationTime Series RegressionLarge Language Model Enhanced Particle Swarm Optimization for Hyperparameter Tuning for Deep Learning Models
Determining the ideal architecture for deep learning models, such as the number of layers and neurons, is a difficult and resource-intensive process that frequently relies on human tuning or computationally costly optimi…
Deep LearningLanguage ModelingLanguage ModellingLarge Language Model+3