most citedTabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2025

LLM Embeddings for Deep Learning on Tabular Data

Boshko Koloski, Andrei Margeloiu, Xiangjian Jiang +3

Tabular deep-learning methods require embedding numerical and categorical input features into high-dimensional spaces before processing them. Existing methods deal with this hetero…

cs.LG2024

TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models

Andrei Margeloiu, Xiangjian Jiang, Nikola Simidjievski +1

Data collection is often difficult in critical fields such as medicine, physics, and chemistry. As a result, classification methods usually perform poorly with these small datasets…