Identifying Organizational Culture for Patient Safety. - Yoo Kyung Boo; Hyeon Sil Lee; Ji Won Park; Seung Woo Ham (FGIT-GDC, 2011)

Hierarchical Inference With Bayesian Neural Networks: An Application to Strong Gravitational Lensing. - Sebastian Wagner-Carena; Ji Won Park; Simon Birrer; Philip J. Marshall; Aaron Roodman; Risa H. Wechsler (CoRR, 2020)

Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant. - Ji Won Park; Sebastian Wagner-Carena; Simon Birrer; Philip J. Marshall; Joshua Yao-Yu Lin; Aaron Roodman (CoRR, 2020)

Inferring Black Hole Properties from Astronomical Multivariate Time Series with Bayesian Attentive Neural Processes. - Ji Won Park; V. Ashley Villar; Yin Li 009; Yan-Fei Jiang; Shirley Ho; Joshua Yao-Yu Lin; Philip J. Marshall; Aaron Roodman (CoRR, 2021)

lenstronomy II: A gravitational lensing software ecosystem. - Simon Birrer; Anowar J. Shajib; Daniel Gilman; Aymeric Galan; Jelle Aalbers; Martin Millon; Robert Morgan; Giulia Pagano; Ji Won Park; Luca Teodori; Nicolas Tessore; Madison Ueland; et al. (J. Open Source Softw., 2021)

Attention-based multiple instance learning with self-supervision to predict microsatellite instability in colorectal cancer from histology whole-slide images. - Jacob S. Leiby; Jie Hao; Gyeong Hoon Kang; Ji Won Park; Dokyoon Kim (EMBC, 2022)

Multi-segment preserving sampling for deep manifold sampler. - Daniel Berenberg; Jae Hyeon Lee; Simon Kelow; Ji Won Park; Andrew M. Watkins; Vladimir Gligorijevic; Richard Bonneau; Stephen Ra; Kyunghyun Cho (CoRR, 2022)

PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design. - Ji Won Park; Samuel Stanton; Saeed Saremi; Andrew M. Watkins; Henri Dwyer; Vladimir Gligorijevic; Richard Bonneau; Stephen Ra; Kyunghyun Cho (CoRR, 2022)

Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks. - Ji Won Park; Simon Birrer; Madison Ueland; Miles D. Cranmer; Adriano Agnello; Sebastian Wagner-Carena; Philip J. Marshall; Aaron Roodman (CoRR, 2022)

GAUCHE: A Library for Gaussian Processes in Chemistry. - Ryan-Rhys Griffiths; Leo Klarner; Henry B. Moss; Aditya Ravuri; Sang Truong; Yuanqi Du; Samuel Stanton; Gary Tom; Bojana Rankovic; Arian Rokkum Jamasb; Aryan Deshwal; Julius Schwartz; et al. (NeurIPS, 2023)

SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers. - Michael Maser; Ji Won Park; Joshua Yao-Yu Lin; Jae Hyeon Lee; Nathan C. Frey; Andrew M. Watkins (CoRR, 2023)

Chain of Log-Concave Markov Chains. - Saeed Saremi; Ji Won Park; Francis R. Bach (ICLR, 2024)

BOtied: Multi-objective Bayesian optimization with tied multivariate ranks. - Ji Won Park; Natasa Tagasovska; Michael Maser; Stephen Ra; Kyunghyun Cho (ICML, 2024)

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design. - Natasa Tagasovska; Ji Won Park; Matthieu Kirchmeyer; Nathan C. Frey; Andrew Martin Watkins; Aya Abdelsalam Ismail; Arian Rokkum Jamasb; Edith Lee; Tyler Bryson; Stephen Ra; Kyunghyun Cho (CoRR, 2024)

Semiparametric conformal prediction. - Ji Won Park; Robert Tibshirani; Kyunghyun Cho (CoRR, 2024)

Blind Biological Sequence Denoising with Self-Supervised Set Learning. - Nathan H. Ng; Ji Won Park; Jae Hyeon Lee; Ryan Lewis Kelly; Stephen Ra; Kyunghyun Cho (Trans. Mach. Learn. Res., 2024)

A multimodal virtual vision platform as a next-generation vision system for a surgical robot. - Young Gyun Kim; Jong Hyeon Lee; Jae Woo Shim; Wounsuk Rhee; Byeong Soo Kim; Dan Yoon; Min Jung Kim; Ji Won Park; Chang Wook Jeong; Han-Kwang Yang; Minwoo Cho; Sungwan Kim (Medical Biol. Eng. Comput., 2024)

Semiparametric conformal prediction. - Ji Won Park; Kyunghyun Cho (AISTATS, 2025)

Supervised Contrastive Block Disentanglement. - Taro Makino; Ji Won Park; Natasa Tagasovska; Takamasa Kudo; Paula Coelho; Jan-Christian Huetter; Heming Yao; Burkhard Hoeckendorf; Ana Carolina Leote; Stephen Ra; David Richmond; Kyunghyun Cho; et al. (CoRR, 2025)

Reliable algorithm selection for machine learning-guided design. - Clara Fannjiang; Ji Won Park (CoRR, 2025)