Lee, Juho

84 publications

ICML 2025 Active Learning with Selective Time-Step Acquisition for PDEs Yegon Kim, Hyunsu Kim, Gyeonghoon Ko, Juho Lee

ICLR 2025 Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series Byoungwoo Park, Hyungi Lee, Juho Lee

NeurIPS 2025 Axial Neural Networks for Dimension-Free Foundation Models Hyunsu Kim, Jonggeon Park, Joan Bruna, Hongseok Yang, Juho Lee

ICML 2025 Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks Dongwoo Lee, Dong Bok Lee, Steven Adriaensen, Juho Lee, Sung Ju Hwang, Frank Hutter, Seon Joo Kim, Hae Beom Lee

NeurIPS 2025 Compact Memory for Continual Logistic Regression Yohan Jung, Hyungi Lee, Wenlong Chen, Thomas Möllenhoff, Yingzhen Li, Juho Lee, Mohammad Emtiyaz Khan

NeurIPS 2025 Cost-Sensitive Freeze-Thaw Bayesian Optimization for Efficient Hyperparameter Tuning Dong Bok Lee, Aoxuan Silvia Zhang, Byungjoo Kim, Junhyeon Park, Steven Adriaensen, Juho Lee, Sung Ju Hwang, Hae Beom Lee

ICLR 2025 Dimension Agnostic Neural Processes Hyungi Lee, Chaeyun Jang, Dong Bok Lee, Juho Lee

ICML 2025 Ensemble Distribution Distillation via Flow Matching Jonggeon Park, Giung Nam, Hyunsu Kim, Jongmin Yoon, Juho Lee

NeurIPS 2025 FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA Seanie Lee, Sangwoo Park, Dong Bok Lee, Dominik Wagner, Haebin Seong, Tobias Bocklet, Juho Lee, Sung Ju Hwang

ICLR 2025 HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models Seanie Lee, Haebin Seong, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang

ICLR 2025 Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain

TMLR 2025 Over-Parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning Francois Caron, Fadhel Ayed, Paul Jung, Hoil Lee, Juho Lee, Hongseok Yang

NeurIPS 2025 PANGEA: Projection-Based Augmentation with Non-Relevant General Data for Enhanced Domain Adaptation in LLMs Seungyoo Lee, Giung Nam, Moonseok Choi, Hyungi Lee, Juho Lee

ICLR 2025 Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo Hyunsu Kim, Giung Nam, Chulhee Yun, Hongseok Yang, Juho Lee

NeurIPS 2025 Reliable Decision‑Making via Calibration‑Oriented Retrieval‑Augmented Generation Chaeyun Jang, Deukhwan Cho, Seanie Lee, Hyungi Lee, Juho Lee

IJCAI 2025 StarFT: Robust Fine-Tuning of Zero-Shot Models via Spuriosity Alignment Younghyun Kim, Jongheon Jeong, Sangkyung Kwak, Kyungmin Lee, Juho Lee, Jinwoo Shin

NeurIPS 2025 Test Time Scaling for Neural Processes Hyungi Lee, Moonseok Choi, Hyunsu Kim, Kyunghyun Cho, Rajesh Ranganath, Juho Lee

ICLR 2025 Variational Bayesian Pseudo-Coreset Hyungi Lee, Seungyoo Lee, Juho Lee

ICML 2024 A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models Taehong Moon, Moonseok Choi, Eunggu Yun, Jongmin Yoon, Gayoung Lee, Jaewoong Cho, Juho Lee

ICMLW 2024 Amortized Probabilistic Detection of Communities in Graphs Yueqi Wang, Yoonho Lee, Pallab Basu, Juho Lee, Yee Whye Teh, Liam Paninski, Ari Pakman

NeurIPSW 2024 Efficient Modeling of Irregular Time-Series with Stochastic Optimal Control Byoungwoo Park, Hyungi Lee, Juho Lee

ICLR 2024 Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling Hyungi Lee, Giung Nam, Edwin Fong, Juho Lee

NeurIPS 2024 Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems Giung Nam, Juho Lee

ICLR 2024 Fast Ensembling with Diffusion Schrödinger Bridge Hyunsu Kim, Jongmin Yoon, Juho Lee

NeurIPSW 2024 Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain

NeurIPS 2024 Learning Infinitesimal Generators of Continuous Symmetries from Data Gyeonghoon Ko, Hyunsu Kim, Juho Lee

ICML 2024 Learning to Explore for Stochastic Gradient MCMC Seunghyun Kim, Seohyeon Jung, Seonghyeon Kim, Juho Lee

ICLR 2024 Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance Giung Nam, Byeongho Heo, Juho Lee

NeurIPS 2024 Model Fusion Through Bayesian Optimization in Language Model Fine-Tuning Chaeyun Jang, Hyungi Lee, Jungtaek Kim, Juho Lee

ECCV 2024 Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion Sanghyun Kim, Seohyeon Jung, Balhae Kim, Moonseok Choi, Jinwoo Shin, Juho Lee

ICLR 2024 Self-Supervised Dataset Distillation for Transfer Learning Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang

ICLR 2024 Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning Moonseok Choi, Hyungi Lee, Giung Nam, Juho Lee

AAAI 2024 Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs Dongjin Lee, Juho Lee, Kijung Shin

ICMLW 2024 Stabilizing the Training of Consistency Models with Score Guidance Jeongjun Lee, Jonggeon Park, Jongmin Yoon, Juho Lee

NeurIPS 2024 Stochastic Optimal Control for Diffusion Bridges in Function Spaces Byoungwoo Park, Jungwon Choi, Sungbin Lim, Juho Lee

ICML 2024 Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts Hyunsu Kim, Yegon Kim, Hongseok Yang, Juho Lee

NeurIPSW 2023 A Generative Self-Supervised Framework Using Functional Connectivity in fMRI Data Jungwon Choi, Seongho Keum, EungGu Yun, Byung-Hoon Kim, Juho Lee

ICLR 2023 A Simple yet Powerful Deep Active Learning with Snapshots Ensembles Seohyeon Jung, Sanghyun Kim, Juho Lee

ICLR 2023 Decoupled Training for Long-Tailed Classification with Stochastic Representations Giung Nam, Sunguk Jang, Juho Lee

JMLR 2023 Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron

NeurIPSW 2023 Deep Neural Networks with Dependent Weights: \\Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron

ICMLW 2023 Early Exiting for Accelerated Inference in Diffusion Models Taehong Moon, Moonseok Choi, EungGu Yun, Jongmin Yoon, Gayoung Lee, Juho Lee

ICLR 2023 Exploring the Role of Mean Teachers in Self-Supervised Masked Auto-Encoders Youngwan Lee, Jeffrey Ryan Willette, Jonghee Kim, Juho Lee, Sung Ju Hwang

NeurIPS 2023 Function Space Bayesian Pseudocoreset for Bayesian Neural Networks Balhae Kim, Hyungi Lee, Juho Lee

ICMLW 2023 Function Space Bayesian Pseudocoreset for Bayesian Neural Networks Balhae Kim, Hyungi Lee, Juho Lee

NeurIPSW 2023 Large-Scale Graph Representation Learning of Dynamic Brain Connectome with Transformers Byung-Hoon Kim, Jungwon Choi, EungGu Yun, Kyungsang Kim, Xiang Li, Juho Lee

ICLR 2023 Martingale Posterior Neural Processes Hyungi Lee, Eunggu Yun, Giung Nam, Edwin Fong, Juho Lee

NeurIPSW 2023 Over-Parameterised Shallow Neural Networks with Asymmetrical Node Scaling: \\ Global Convergence Guarantees and Feature Learning Fadhel Ayed, Francois Caron, Paul Jung, Juho Lee, Hoil Lee, Hongseok Yang

ICML 2023 Probabilistic Imputation for Time-Series Classification with Missing Data Seunghyun Kim, Hyunsu Kim, Eunggu Yun, Hwangrae Lee, Jaehun Lee, Juho Lee

ICML 2023 Regularizing Towards Soft Equivariance Under Mixed Symmetries Hyunsu Kim, Hyungi Lee, Hongseok Yang, Juho Lee

ICML 2023 Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation Jeffrey Willette, Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang

ICLR 2023 Self-Distillation for Further Pre-Training of Transformers Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi

ICMLW 2023 Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models Sanghyun Kim, Seohyeon Jung, Balhae Kim, Moonseok Choi, Jinwoo Shin, Juho Lee

ICML 2023 Traversing Between Modes in Function Space for Fast Ensembling Eunggu Yun, Hyungi Lee, Giung Nam, Juho Lee

NeurIPSW 2022 Fine-Tuning Diffusion Models with Limited Data Taehong Moon, Moonseok Choi, Gayoung Lee, Jung-Woo Ha, Juho Lee

ICML 2022 Improving Ensemble Distillation with Weight Averaging and Diversifying Perturbation Giung Nam, Hyungi Lee, Byeongho Heo, Juho Lee

ICLR 2022 Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty Jeffrey Ryan Willette, Hae Beom Lee, Juho Lee, Sung Ju Hwang

NeurIPS 2022 On Divergence Measures for Bayesian Pseudocoresets Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha, Juho Lee

ICLR 2022 Scale Mixtures of Neural Network Gaussian Processes Hyungi Lee, Eunggu Yun, Hongseok Yang, Juho Lee

ICLR 2022 Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning Seanie Lee, Hae Beom Lee, Juho Lee, Sung Ju Hwang

ICML 2022 Set Based Stochastic Subsampling Bruno Andreis, Seanie Lee, A. Tuan Nguyen, Juho Lee, Eunho Yang, Sung Ju Hwang

NeurIPS 2022 Set-Based Meta-Interpolation for Few-Task Meta-Learning Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang

ICCV 2021 A Multi-Mode Modulator for Multi-Domain Few-Shot Classification Yanbin Liu, Juho Lee, Linchao Zhu, Ling Chen, Humphrey Shi, Yi Yang

ICML 2021 Adversarial Purification with Score-Based Generative Models Jongmin Yoon, Sung Ju Hwang, Juho Lee

NeurIPS 2021 Diversity Matters When Learning from Ensembles Giung Nam, Jongmin Yoon, Yoonho Lee, Juho Lee

NeurIPS 2021 Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding Andreis Bruno, Jeffrey Willette, Juho Lee, Sung Ju Hwang

CVPR 2021 SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data Jinwoo Kim, Jaehoon Yoo, Juho Lee, Seunghoon Hong

NeurIPS 2020 Bootstrapping Neural Processes Juho Lee, Yoonho Lee, Jungtaek Kim, Eunho Yang, Sung Ju Hwang, Yee Whye Teh

ICML 2020 Cost-Effective Interactive Attention Learning with Neural Attention Processes Jay Heo, Junhyeon Park, Hyewon Jeong, Kwang Joon Kim, Juho Lee, Eunho Yang, Sung Ju Hwang

ICLR 2020 Deep Amortized Clustering Juho Lee, Yoonho Lee, Yee Whye Teh

AAAI 2020 Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare Ingyo Chung, Saehoon Kim, Juho Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang

NeurIPS 2020 Neural Complexity Measures Yoonho Lee, Juho Lee, Sung Ju Hwang, Eunho Yang, Seungjin Choi

AISTATS 2019 A Bayesian Model for Sparse Graphs with Flexible Degree Distribution and Overlapping Community Structure Juho Lee, Lancelot James, Seungjin Choi, Francois Caron

ICML 2019 Beyond the Chinese Restaurant and Pitman-Yor Processes: Statistical Models with Double Power-Law Behavior Fadhel Ayed, Juho Lee, Francois Caron

ICLR 2019 Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Eunho Yang, Sung Ju Hwang, Yi Yang

ICML 2019 Set Transformer: A Framework for Attention-Based Permutation-Invariant Neural Networks Juho Lee, Yoonho Lee, Jungtaek Kim, Adam Kosiorek, Seungjin Choi, Yee Whye Teh

NeurIPS 2018 DropMax: Adaptive Variational SoftMax Hae Beom Lee, Juho Lee, Saehoon Kim, Eunho Yang, Sung Ju Hwang

NeurIPS 2018 Uncertainty-Aware Attention for Reliable Interpretation and Prediction Jay Heo, Hae Beom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang, Sung Ju Hwang

ICML 2017 Bayesian Inference on Random Simple Graphs with Power Law Degree Distributions Juho Lee, Creighton Heaukulani, Zoubin Ghahramani, Lancelot F. James, Seungjin Choi

NeurIPS 2016 Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models Juho Lee, Lancelot F James, Seungjin Choi

AISTATS 2015 Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility Juho Lee, Seungjin Choi

NeurIPS 2015 Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models Juho Lee, Seungjin Choi

AISTATS 2014 Incremental Tree-Based Inference with Dependent Normalized Random Measures Juho Lee, Seungjin Choi

ECCV 2012 Online Video Segmentation by Bayesian Split-Merge Clustering Juho Lee, Suha Kwak, Bohyung Han, Seungjin Choi