:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hong, Sungchul, An, Seunghwan, Jeon, Jong-June
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2405.19757
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis
by: An, Seunghwan, et al.
Published: (2024)

Uniform Pessimistic Risk and its Optimal Portfolio
by: Hong, Sungchul, et al.
Published: (2023)

Interpretable Water Level Forecaster with Spatiotemporal Causal Attention Mechanisms
by: Hong, Sungchul, et al.
Published: (2023)

Estimating Subgraph Importance with Structural Prior Domain Knowledge
by: Kim, Changhyun, et al.
Published: (2026)

Unicorn: U-Net for Sea Ice Forecasting with Convolutional Neural Ordinary Differential Equations
by: Park, Jaesung, et al.
Published: (2024)

Theoretical Convergence of SMOTE-Generated Samples
by: Kamalov, Firuz, et al.
Published: (2026)

MAGNET: Autonomous Expert Model Generation via Decentralized Autoresearch and BitNet Training
by: Kim, Yongwan, et al.
Published: (2026)

Continuous Fair SMOTE -- Fairness-Aware Stream Learning from Imbalanced Data
by: Lammers, Kathrin, et al.
Published: (2025)

Simplicial SMOTE: Oversampling Solution to the Imbalanced Learning Problem
by: Kachan, Oleg, et al.
Published: (2025)

AxelSMOTE: An Agent-Based Oversampling Algorithm for Imbalanced Classification
by: Kishanthan, Sukumar, et al.
Published: (2025)

Comparative Analysis of MDL-VAE vs. Standard VAE on 202 Years of Gynecological Data
by: Santos, Paula
Published: (2025)

Augmenting The Weather: A Hybrid Counterfactual-SMOTE Algorithm for Improving Crop Growth Prediction When Climate Changes
by: Temraz, Mohammed, et al.
Published: (2025)

Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data
by: Shahzad, Muhammad Khuram, et al.
Published: (2026)

Enhancing Machine Learning for Imbalanced Medical Data: A Quantum-Inspired Approach to Synthetic Oversampling (QI-SMOTE)
by: Kashtriya, Vikas, et al.
Published: (2025)

HyperSMOTE: A Hypergraph-based Oversampling Approach for Imbalanced Node Classifications
by: Zhao, Ziming, et al.
Published: (2024)

A Quantum Approach to Synthetic Minority Oversampling Technique (SMOTE)
by: Mohanty, Nishikanta, et al.
Published: (2024)

Precision Tracked Transformer via Kalman Filtering, Kriging and Process Noise
by: Long, Bo, et al.
Published: (2026)

Advanced Payment Security System:XGBoost, LightGBM and SMOTE Integrated
by: Zheng, Qi, et al.
Published: (2024)

Preventing Model Collapse via Contraction-Conditioned Neural Filters
by: Han, Zongjian, et al.
Published: (2025)

Iterative Amortized Hierarchical VAE
by: Penninga, Simon W., et al.
Published: (2026)

Aligning AI Agents via Information-Directed Sampling
by: Jeon, Hong Jun, et al.
Published: (2024)

Improving Ensemble Forecasts of Abnormally Deflecting Tropical Cyclones with Fused Atmosphere-Ocean-Terrain Data
by: Li, Qixiang, et al.
Published: (2026)

Meta-Ensemble Learning with Diverse Data Splits for Improved Respiratory Sound Classification
by: Kim, June-Woo, et al.
Published: (2026)

VP-VAE: Rethinking Vector Quantization via Adaptive Vector Perturbation
by: Zhai, Linwei, et al.
Published: (2026)

Towards Improving Long-Tail Entity Predictions in Temporal Knowledge Graphs through Global Similarity and Weighted Sampling
by: Mirtaheri, Mehrnoosh, et al.
Published: (2025)

On the Mechanisms of Collaborative Learning in VAE Recommenders
by: Vuong, Tung-Long, et al.
Published: (2025)

Bounding Evidence and Estimating Log-Likelihood in VAE
by: Struski, Łukasz, et al.
Published: (2022)

MO-RiskVAE: A Multi-Omics Variational Autoencoder for Survival Risk Modeling in Multiple MyelomaMO-RiskVAE
by: Chen, Zixuan, et al.
Published: (2026)

ED-VAE: Entropy Decomposition of ELBO in Variational Autoencoders
by: Lygerakis, Fotios, et al.
Published: (2024)

Filter then Attend: Improving attention-based Time Series Forecasting with Spectral Filtering
by: Dayag, Elisha, et al.
Published: (2025)

AdapTable: Test-Time Adaptation for Tabular Data via Shift-Aware Uncertainty Calibrator and Label Distribution Handler
by: Kim, Changhun, et al.
Published: (2024)

Structural Equation-VAE: Disentangled Latent Representations for Tabular Data
by: Zhang, Ruiyu, et al.
Published: (2025)

Enhancing Topological Dependencies in Spatio-Temporal Graphs with Cycle Message Passing Blocks
by: Lee, Minho, et al.
Published: (2024)

TABCF: Counterfactual Explanations for Tabular Data Using a Transformer-Based VAE
by: Panagiotou, Emmanouil, et al.
Published: (2024)

FLoRA: Fused forward-backward adapters for parameter efficient fine-tuning and reducing inference-time latencies of LLMs
by: Gowda, Dhananjaya, et al.
Published: (2025)

VAEneu: A New Avenue for VAE Application on Probabilistic Forecasting
by: Koochali, Alireza, et al.
Published: (2024)

HiVAE: Hierarchical Latent Variables for Scalable Theory of Mind
by: Doering, Nigel, et al.
Published: (2026)

Fusing Urban Structure and Semantics: A Conditional Diffusion Model for Cross-City OD Matrix Generation
by: Chen, Bin, et al.
Published: (2026)

Information-Theoretic Foundations for Neural Scaling Laws
by: Jeon, Hong Jun, et al.
Published: (2024)

Information-Theoretic Foundations for Machine Learning
by: Jeon, Hong Jun, et al.
Published: (2024)