Junghyo Jo - RankMe

28 papers A* 2Journal 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Variational Garrote for Sparse Inverse Problems. CoRR KangHun Lee, Hyungjoon Soh, Junghyo Jo
2025	J	`jnl`	Data augmentation using diffusion models to enhance inverse Ising inference. CoRR Yechan Lim, Sangwon Lee, Junghyo Jo
2025	J	`jnl`	Multiplicative Learning. CoRR Han Kim, Hyungjoon Soh, Vipul Periwal, Junghyo Jo
2025	J	`jnl`	Stochastic Clock Attention for Aligning Continuous and Ordered Sequences. CoRR Hyungjoon Soh, Junghyo Jo
2025	J	`jnl`	Variational Garrote for Statistical Physics-based Sparse and Robust Variable Selection. CoRR Hyungjoon Soh, Dongha Lee, Vipul Periwal, Junghyo Jo
2024	J	`jnl`	Annealing approach to root-finding. CoRR Junghyo Jo, Alexandre Wagemakers, Vipul Periwal
2024	A*	`conf`	Direct Unlearning Optimization for Robust and Safe Text-to-Image Models. NeurIPS Yong-Hyun Park, Sangdoo Yun, Jin-Hwa Kim, Junho Kim, Geonhui Jang, Yonghyun Jeong, Junghyo Jo, Gayoung Lee
2024	J	`jnl`	Direct Unlearning Optimization for Robust and Safe Text-to-Image Models. CoRR Yong-Hyun Park, Sangdoo Yun, Jin-Hwa Kim, Junho Kim, Geonhui Jang, Yonghyun Jeong, Junghyo Jo, Gayoung Lee
2024	J	`jnl`	Geometric Remove-and-Retrain (GOAR): Coordinate-Invariant eXplainable AI Assessment. CoRR Yong-Hyun Park, Junghoon Seo, Bomseok Park, Seongsu Lee, Junghyo Jo
2024	J	`jnl`	Neural Graph Simulator for Complex Systems. CoRR Hoyun Choi, Sungyeop Lee, B. Kahng, Junghyo Jo
2024	J	`jnl`	Resolution Chromatography of Diffusion Models. CoRR Juno Hwang, Yong-Hyun Park, Junghyo Jo
2024	J	`jnl`	Upsample Guidance: Scale Up Diffusion Models without Training. CoRR Juno Hwang, Yong-Hyun Park, Junghyo Jo
2023	J	`jnl`	GNRK: Graph Neural Runge-Kutta method for solving partial differential equations. CoRR Hoyun Choi, Sungyeop Lee, B. Kahng, Junghyo Jo
2023	J	`jnl`	Mirror Descent of Hopfield Model. Neural Comput. Hyungjoon Soh, Dongyeob Kim, Juno Hwang, Junghyo Jo
2023	J	`jnl`	Tradeoff of generalization error in unsupervised learning. CoRR Gilhan Kim, Hojun Lee, Junghyo Jo, Yongjoo Baek
2023	A*	`conf`	Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry. NeurIPS Yong-Hyun Park, Mingi Kwon, Jaewoong Choi, Junghyo Jo, Youngjung Uh
2023	J	`jnl`	Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry. CoRR Yong-Hyun Park, Mingi Kwon, Jaewoong Choi, Junghyo Jo, Youngjung Uh
2023	J	`jnl`	Unsupervised Discovery of Semantic Latent Directions in Diffusion Models. CoRR Yong-Hyun Park, Mingi Kwon, Junghyo Jo, Youngjung Uh
2022	J	`jnl`	Mirror descent of Hopfield model. CoRR Hyungjoon Soh, Dongyeob Kim, Juno Hwang, Junghyo Jo
2021	J	`jnl`	Compression phase is not necessary for generalization in representation learning. CoRR Sungyeop Lee, Junghyo Jo
2021	J	`jnl`	Information Flows of Diverse Autoencoders. Entropy Sungyeop Lee, Junghyo Jo
2021	J	`jnl`	Scale-invariant representation of machine learning. CoRR Sungyeop Lee, Junghyo Jo
2020	J	`jnl`	Machine learning for the diagnosis of early stage diabetes using temporal glucose profiles. CoRR Woo-Seok Lee, Junghyo Jo, Taegeun Song
2020	J	`jnl`	Tractable loss function and color image generation of multinary restricted Boltzmann machine. CoRR Juno Hwang, Wonseok Hwang, Junghyo Jo
2019	J	`jnl`	Inverse Ising inference from high-temperature re-weighting of observations. CoRR Junghyo Jo, Danh-Tai Hoang, Vipul Periwal
2017	J	`jnl`	Emergence and Relevance of Criticality in Deep Learning. CoRR Juyong Song, Matteo Marsili, Junghyo Jo
2015	J	`jnl`	Minimal Perceptrons for Memorizing Complex Patterns. CoRR Marissa Pastor, Juyong Song, Danh-Tai Hoang, Junghyo Jo
2009	J	`jnl`	Hypertrophy and/or Hyperplasia: Dynamics of Adipose Tissue Growth. PLoS Comput. Biol. Junghyo Jo, Oksana Gavrilova, Stephanie Pack, William Jou, Shawn Mullen, Anne E. Sumner, Samuel W. Cushman, Vipul Periwal