Hypertrophy and/or Hyperplasia: Dynamics of Adipose Tissue Growth. - Junghyo Jo; Oksana Gavrilova; Stephanie Pack; William Jou; Shawn Mullen; Anne E. Sumner; Samuel W. Cushman; Vipul Periwal (PLoS Comput. Biol., 2009)

Minimal Perceptrons for Memorizing Complex Patterns. - Marissa Pastor; Juyong Song; Danh-Tai Hoang; Junghyo Jo (CoRR, 2015)

Emergence and Relevance of Criticality in Deep Learning. - Juyong Song; Matteo Marsili; Junghyo Jo (CoRR, 2017)

Inverse Ising inference from high-temperature re-weighting of observations. - Junghyo Jo; Danh-Tai Hoang; Vipul Periwal (CoRR, 2019)

Machine learning for the diagnosis of early stage diabetes using temporal glucose profiles. - Woo-Seok Lee; Junghyo Jo; Taegeun Song (CoRR, 2020)

Tractable loss function and color image generation of multinary restricted Boltzmann machine. - Juno Hwang; Wonseok Hwang; Junghyo Jo (CoRR, 2020)

Compression phase is not necessary for generalization in representation learning. - Sungyeop Lee; Junghyo Jo (CoRR, 2021)

Scale-invariant representation of machine learning. - Sungyeop Lee; Junghyo Jo (CoRR, 2021)

Information Flows of Diverse Autoencoders. - Sungyeop Lee; Junghyo Jo (Entropy, 2021)

Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry. - Yong-Hyun Park; Mingi Kwon; Jaewoong Choi; Junghyo Jo; Youngjung Uh (NeurIPS, 2023)

Unsupervised Discovery of Semantic Latent Directions in Diffusion Models. - Yong-Hyun Park; Mingi Kwon; Junghyo Jo; Youngjung Uh (CoRR, 2023)

Tradeoff of generalization error in unsupervised learning. - Gilhan Kim; Hojun Lee; Junghyo Jo; Yongjoo Baek (CoRR, 2023)

GNRK: Graph Neural Runge-Kutta method for solving partial differential equations. - Hoyun Choi; Sungyeop Lee; B. Kahng; Junghyo Jo (CoRR, 2023)

Mirror Descent of Hopfield Model. - Hyungjoon Soh; Dongyeob Kim; Juno Hwang; Junghyo Jo (Neural Comput., 2023)

Direct Unlearning Optimization for Robust and Safe Text-to-Image Models. - Yong-Hyun Park; Sangdoo Yun; Jin-Hwa Kim; Junho Kim; Geonhui Jang; Yonghyun Jeong; Junghyo Jo; Gayoung Lee (NeurIPS, 2024)

Resolution Chromatography of Diffusion Models. - Juno Hwang; Yong-Hyun Park; Junghyo Jo (CoRR, 2024)

Upsample Guidance: Scale Up Diffusion Models without Training. - Juno Hwang; Yong-Hyun Park; Junghyo Jo (CoRR, 2024)

Annealing approach to root-finding. - Junghyo Jo; Alexandre Wagemakers; Vipul Periwal (CoRR, 2024)

Geometric Remove-and-Retrain (GOAR): Coordinate-Invariant eXplainable AI Assessment. - Yong-Hyun Park; Junghoon Seo; Bomseok Park; Seongsu Lee; Junghyo Jo (CoRR, 2024)

Neural Graph Simulator for Complex Systems. - Hoyun Choi; Sungyeop Lee; B. Kahng; Junghyo Jo (CoRR, 2024)

Multiplicative Learning. - Han Kim; Hyungjoon Soh; Vipul Periwal; Junghyo Jo (CoRR, 2025)

Data augmentation using diffusion models to enhance inverse Ising inference. - Yechan Lim; Sangwon Lee; Junghyo Jo (CoRR, 2025)