Seunghan Lee

Seunghan Lee

Deep Learning, Data Science, Statistics

TAB

MissDiff; Training Diffusion Models on Tabular Data with Missing Values

2 minute read

ICML 2023 Workshop

Diffusion Models for Tabular Data Imputation and Synthetic Data Generation

3 minute read

ICML 2024 (?)

CoDi; Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis

3 minute read

ICML 2023

STASY; Score-based Tabular Data Synthesis

5 minute read

ICLR 2023

TabDDPM; Modeling Tabular Data with Diffusion Models

5 minute read

ICML 2023

Transfer Learning with Deep Tabular Models

2 minute read

ICLR 2023

On Embeddings for Numerical Features in Tabular Deep Learning

2 minute read

NeurIPS 2022

Neural Oblivious Decision Ensembles for DL on Tabular Data

2 minute read

ICLR 2020

Revisiting Deep Learning Models for Tabular Data

3 minute read

FT Transformer(NeurIPS 2021)

TransTab; Learnable Transferable Tabular Transformers across Tables

5 minute read

TransTab (NeurIPS 2022)

SAINT; Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-training

8 minute read

SAINT

TabTransformer; Tabular Data Modeling Using Contextual Embeddings

5 minute read

TabTransformer

Semi-SL & Self-SL for Tabular Data

3 minute read

VIME, SubTab, SCARF, Contrastive Mixup

(paper 52) CORE

1 minute read

2021

(paper 51) TabNet

2 minute read

2021

(paper 50) Contrastive Mixup

4 minute read

2021

(paper 49) VIME

7 minute read

2020