1. Inference on Gaussian mixture models with dependent labels,

Seunghyun Lee, Rajarshi Mukherjee and Sumit Mukherjee, (a-b)

in preparation, 2025+.

2. CLT in high-dimensional Bayesian linear regression with low SNR,

Seunghyun Lee, Nabarun Deb and Sumit Mukherjee,

submitted, 2025. [arXiv]

3. Identifiability of latent causal graphical models without pure children,

Seunghyun Lee and Yuqi Gu,

submitted, 2025. [arXiv]

4. Fluctuations in random field Ising models,

Seunghyun Lee, Nabarun Deb and Sumit Mukherjee,

submitted, 2025. [arXiv]

5. Deep Discrete Encoders: identifiable deep generative models for rich data with discrete latent layers,

Seunghyun Lee and Yuqi Gu, 

under revision, 2025. [arXiv], [code]

6. Exploratory general-response cognitive diagnostic models with higher-order structures,

Jia Liu, Seunghyun Lee and Yuqi Gu,

Psychometrika, 2025. [Journal], [pdf]

7. New paradigm of identifiability in cognitive diagnostic models: beyond categorical responses,

Seunghyun Lee and Yuqi Gu,

Psychometrika, 89(4): 1304-1336, 2024. [Journal], [code]

8. Latent conjunctive Bayesian network: unify attribute hierarchy and Bayesian network for cognitive diagnosis, 

Seunghyun Lee and Yuqi Gu, 

Annals of Applied Statistics, 18(3): 1988-2011, 2024. [Journal], [arXiv], [code]

9. Conditions for bubbles to arise under heterogeneous beliefs,

Seunghyun Lee and Hyungbin Park,

Quantitative Finance (Feature article), 22(3): 409-421, 2022. [Journal], [arXiv]

10. A modified Cahn-Hilliard equation for 3D volume reconstruction from two planar cross sections,

Seunggyu Lee et. al,

J. KSIAM, 19(1): 47-56, 2015. [Journal]

Gaussian mixture models with dependent labels - Northeast Probability Seminar (NEPS), Columbia University, NY (Nov 2024) [slides]

Latent conjunctive Bayesian network - International Meeting of the Psychometric Society (IMPS), Prague, Czech Republic (July 2024) [poster]

New paradigm of general-response cognitive diagnostic models - International Meeting of the Psychometric Society (IMPS), University of Maryland, MD (July 2023) [slides]