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20192026
most citedDeep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions

2 citations · 2 across the 6 of their papers we have counts for

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cs.LG2026

PAC-Bayes Beyond Parameter Space: Behavioral Equivalence, Z-Information, and Exact Complexity Decomposition

Vasant G. Honavar, Satish Kumar Keshri, Neil Ashtekar +1

PAC-Bayes theory provides generalization guarantees by controlling the Kullback--Leibler (KL) divergence between posterior and prior distributions over a chosen hypothesis represen…

cs.LG2025

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models

Weijieying Ren, Jingxi Zhu, Zehao Liu +2

Artificial intelligence (AI) has demonstrated significant potential in transforming healthcare through the analysis and modeling of electronic health records (EHRs). However, the i…

cs.LG20252 cited

Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions

Weijieying Ren, Tianxiang Zhao, Yuqing Huang +1

Tabular data remains one of the most prevalent data types across a wide range of real-world applications, yet effective representation learning for this domain poses unique challen…

cs.LG2025

C-HDNet: Hyperdimensional Computing for Causal Effect Estimation from Observational Data Under Network Interference

Abhishek Dalvi, Neil Ashtekar, Vasant Honavar

We address the problem of estimating causal effects from observational data in the presence of network confounding, a setting where both treatment assignment and observed outcomes…

cs.LG2019

The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario

Thanh Le, Vasant Honavar

The Dynamical Gaussian Process Latent Variable Models provide an elegant non-parametric framework for learning the low dimensional representations of the high-dimensional time-seri…