Cover Image

Highly Imbalanced Regression with Tabular Data in SEP and Other Applications

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Moukpe, Josias K., Chan, Philip K., Zhang, Ming
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Imbalance in Regression Datasets
by: Kowatsch, Daniel, et al.
Published: (2024)

Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study
by: Panagiotou, Emmanouil, et al.
Published: (2024)

On Imbalanced Regression with Hoeffding Trees
by: Alchirch, Pantia-Marina, et al.
Published: (2026)

EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models
by: Kim, Jinhee, et al.
Published: (2024)

DNN-GDITD: Out-of-distribution detection via Deep Neural Network based Gaussian Descriptor for Imbalanced Tabular Data
by: Chudasama, Priyanka, et al.
Published: (2024)

Tabular Data with Class Imbalance: Predicting Electric Vehicle Crash Severity with Pretrained Transformers (TabPFN) and Mamba-Based Models
by: Somvanshi, Shriyank, et al.
Published: (2025)

SMOGAN: Synthetic Minority Oversampling with GAN Refinement for Imbalanced Regression
by: Alahyari, Shayan, et al.
Published: (2025)

Error Distribution Smoothing:Advancing Low-Dimensional Imbalanced Regression
by: Chen, Donghe, et al.
Published: (2025)

PMLBmini: A Tabular Classification Benchmark Suite for Data-Scarce Applications
by: Knauer, Ricardo, et al.
Published: (2024)

Revisiting Chebyshev Polynomial and Anisotropic RBF Models for Tabular Regression
by: Gerber, Luciano, et al.
Published: (2026)

ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing
by: Madhusudhanan, Kiran, et al.
Published: (2024)

TabGen-ICL: Residual-Aware In-Context Example Selection for Tabular Data Generation
by: Fang, Liancheng, et al.
Published: (2025)

Discovering Association Rules in High-Dimensional Small Tabular Data
by: Karabulut, Erkan, et al.
Published: (2025)

Team, Then Trim: An Assembly-Line LLM Framework for High-Quality Tabular Data Generation
by: Zhang, Congjing, et al.
Published: (2026)

Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework
by: Tu, Ruibo, et al.
Published: (2024)

Universal Embeddings of Tabular Data
by: Franz, Astrid, et al.
Published: (2025)

An Explainable Gaussian Process Auto-encoder for Tabular Data
by: Zhang, Wei, et al.
Published: (2025)

Offline Reinforcement Learning with Imbalanced Datasets
by: Jiang, Li, et al.
Published: (2023)

Towards Synthesizing High-Dimensional Tabular Data with Limited Samples
by: Li, Zuqing, et al.
Published: (2025)

ART: Adaptive Resampling-based Training for Imbalanced Classification
by: Basandrai, Arjun, et al.
Published: (2025)

Deep Feature Embedding for Tabular Data
by: Wu, Yuqian, et al.
Published: (2024)

Automated Model Selection for Tabular Data
by: Amballa, Avinash, et al.
Published: (2024)

Enhancing Performance for Highly Imbalanced Medical Data via Data Regularization in a Federated Learning Setting
by: Tsoumplekas, Georgios, et al.
Published: (2024)

SEMRes-DDPM: Residual Network Based Diffusion Modelling Applied to Imbalanced Data
by: Zheng, Ming, et al.
Published: (2024)

A Cost-Sensitive Transformer Model for Prognostics Under Highly Imbalanced Industrial Data
by: Beikmohammadi, Ali, et al.
Published: (2024)

DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data
by: Habib, Al Zadid Sultan Bin, et al.
Published: (2026)

QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptation
by: Zheng, Kangyu, et al.
Published: (2025)

Squeezing Lemons with Hammers: An Evaluation of AutoML and Tabular Deep Learning for Data-Scarce Classification Applications
by: Knauer, Ricardo, et al.
Published: (2024)

Data-Efficient Symbolic Regression via Foundation Model Distillation
by: Ying, Wangyang, et al.
Published: (2025)

TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression
by: Madhusudhanan, Kiran, et al.
Published: (2025)

LLM Embeddings for Deep Learning on Tabular Data
by: Koloski, Boshko, et al.
Published: (2025)

Distributional Regression with Tabular Foundation Models: Evaluating Probabilistic Predictions via Proper Scoring Rules
by: Landsgesell, Jonas, et al.
Published: (2026)

Tabular Data Generation using Binary Diffusion
by: Kinakh, Vitaliy, et al.
Published: (2024)

HyperFast: Instant Classification for Tabular Data
by: Bonet, David, et al.
Published: (2024)

Interpretable Graph Neural Networks for Tabular Data
by: Alkhatib, Amr, et al.
Published: (2023)

Fully Test-time Adaptation for Tabular Data
by: Zhou, Zhi, et al.
Published: (2024)

Pure Node Selection for Imbalanced Graph Node Classification
by: Zeng, Fanlong, et al.
Published: (2025)

StructSynth: Leveraging LLMs for Structure-Aware Tabular Data Synthesis in Low-Data Regimes
by: Liu, Siyi, et al.
Published: (2025)

Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators
by: Bai, Sikai, et al.
Published: (2023)

Data-Free Generative Replay for Class-Incremental Learning on Imbalanced Data
by: Younis, Sohaib, et al.
Published: (2024)