Multi-target regression
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Benchmarks
Most implemented
Materials Representation and Transfer Learning for Multi-Property Prediction
Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis
Utilizing Data Fingerprints for Privacy-Preserving Algorithm Selection in Time Series Classification: Performance and Uncertainty Estimation on Unseen Datasets
TMPNN: High-Order Polynomial Regression Based on Taylor Map Factorization
Local Interpretability of Random Forests for Multi-Target Regression
Papers
Scaling-Score Conformal Prediction for Multi-Target Regression
Multi-target regression requires a model to simultaneously predict several related outputs. Conformal prediction provides distribution-free, finite-sample marginal coverage guarantees, but extending these to joint multi-…
Multi-target regressionDecoding Naturalistic Emotion Dynamics from the Brain: An LLM-Enhanced Regression Framework
Decoding emotional states from neural signals has been typically framed as a discrete, single-label classification task based on emotionally stable stimuli, a formulation that oversimplifies the continuous, fluid, and co…
Multi-target regressionInterpretable Multivariate Conformal Prediction with Fast Transductive Standardization
We propose a conformal prediction method for constructing tight simultaneous prediction intervals for multiple, potentially related, numerical outputs given a single input. This method can be combined with any multi-targ…
Multi-target regressionDeep Imbalanced Multi-Target Regression: 3D Point Cloud Voxel Content Estimation in Simulated Forests
Voxelization is an effective approach to reduce the computational cost of processing Light Detection and Ranging (LiDAR) data, yet it results in a loss of fine-scale structural information. This study explores whether lo…
Multi-target regressionImage GenerationPoint CloudsRegularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis
In this paper, we address the task of characterizing the chemical composition of planetary surfaces using convolutional neural networks (CNNs). Specifically, we seek to predict the multi-oxide weights of rock samples bas…
Multi-target regressionUtilizing Data Fingerprints for Privacy-Preserving Algorithm Selection in Time Series Classification: Performance and Uncertainty Estimation on Unseen Datasets
The selection of algorithms is a crucial step in designing AI services for real-world time series classification use cases. Traditional methods such as neural architecture search, automated machine learning, combined alg…
Multi-target regressionNeural Architecture SearchPrivacy PreservingTime Series+1