Juho Lee

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 56

Top Topics

Transfer Learning

Diffusion Models

Top Venues

Publications

Dongjin Lee, Juho Lee, Kijung Shin
Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs. AAAI (2024)
Giung Nam, Byeongho Heo, Juho Lee
Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance. ICLR (2024)
Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
Self-Supervised Dataset Distillation for Transfer Learning. ICLR (2024)
Hyungi Lee, Giung Nam, Edwin Fong, Juho Lee
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling. CoRR (2024)
Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain
Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR (2024)
Sanghyun Kim, Seohyeon Jung, Balhae Kim, Moonseok Choi, Jinwoo Shin, Juho Lee
Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion. CoRR (2024)
Hyungi Lee, Giung Nam, Edwin Fong, Juho Lee
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling. ICLR (2024)
Jongmin Yoon, Juho Lee
Sequential Flow Straightening for Generative Modeling. CoRR (2024)
Jungwon Choi, Hyungi Lee, Byung-Hoon Kim, Juho Lee
Joint-Embedding Masked Autoencoder for Self-supervised Learning of Dynamic Functional Connectivity from the Human Brain. CoRR (2024)
Hyunsu Kim, Jongmin Yoon, Juho Lee
Fast Ensembling with Diffusion Schr\"odinger Bridge. CoRR (2024)
Hyunsu Kim, Jongmin Yoon, Juho Lee
Fast Ensembling with Diffusion Schrödinger Bridge. ICLR (2024)
Moonseok Choi, Hyungi Lee, Giung Nam, Juho Lee
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning. ICLR (2024)
Dong Bok Lee, Aoxuan Silvia Zhang, Byungjoo Kim, Junhyeon Park, Juho Lee, Sung Ju Hwang, Hae Beom Lee
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation. CoRR (2024)
Giung Nam, Byeongho Heo, Juho Lee
Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance. CoRR (2024)
Hyungi Lee, Eunggu Yun, Giung Nam, Edwin Fong, Juho Lee
Martingale Posterior Neural Processes. CoRR (2023)
Moonseok Choi, Hyungi Lee, Giung Nam, Juho Lee
SWAMP: Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning. CoRR (2023)
Eunggu Yun, Hyungi Lee, Giung Nam, Juho Lee
Traversing Between Modes in Function Space for Fast Ensembling. CoRR (2023)
Balhae Kim, Hyungi Lee, Juho Lee
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks. CoRR (2023)
Byung-Hoon Kim, Jungwon Choi, Eunggu Yun, Kyungsang Kim, Xiang Li, Juho Lee
Large-scale Graph Representation Learning of Dynamic Brain Connectome with Transformers. CoRR (2023)
Dongjin Lee, Juho Lee, Kijung Shin
Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs. CoRR (2023)
Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi
Self-Distillation for Further Pre-training of Transformers. ICLR (2023)
Eunggu Yun, Hyungi Lee, Giung Nam, Juho Lee
Traversing Between Modes in Function Space for Fast Ensembling. ICML (2023)
Sanghyun Kim, Seohyeon Jung, Balhae Kim, Moonseok Choi, Jinwoo Shin, Juho Lee
Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models. CoRR (2023)
Balhae Kim, Hyungi Lee, Juho Lee
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks. NeurIPS (2023)
Giung Nam, Sunguk Jang, Juho Lee
Decoupled Training for Long-Tailed Classification With Stochastic Representations. CoRR (2023)
Seongho Keum, Sanghyun Kim, Soojeong Lee, Juho Lee
Slot-Mixup with Subsampling: A Simple Regularization for WSI Classification. CoRR (2023)
Jungwon Choi, Seongho Keum, EungGu Yun, Byung-Hoon Kim, Juho Lee
A Generative Self-Supervised Framework using Functional Connectivity in fMRI Data. CoRR (2023)
Youngwan Lee, Jeffrey Ryan Willette, Jonghee Kim, Juho Lee, Sung Ju Hwang
Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders. ICLR (2023)
Seunghyun Kim, Hyunsu Kim, Eunggu Yun, Hwangrae Lee, Jaehun Lee, Juho Lee
Probabilistic Imputation for Time-series Classification with Missing Data. CoRR (2023)
Seunghyun Kim, Hyunsu Kim, Eunggu Yun, Hwangrae Lee, Jaehun Lee, Juho Lee
Probabilistic Imputation for Time-series Classification with Missing Data. ICML (2023)
Hyunsu Kim, Hyungi Lee, Hongseok Yang, Juho Lee
Regularizing Towards Soft Equivariance Under Mixed Symmetries. ICML (2023)
Giung Nam, Sunguk Jang, Juho Lee
Decoupled Training for Long-Tailed Classification With Stochastic Representations. ICLR (2023)
Sanghyun Kim, Jungwon Choi, NamHee Kim, Jaesung Ryu, Juho Lee
Modeling Uplift from Observational Time-Series in Continual Scenarios. AAAI Bridge Program (2023)
Seohyeon Jung, Sanghyun Kim, Juho Lee
A Simple Yet Powerful Deep Active Learning With Snapshots Ensembles. ICLR (2023)
Hyungi Lee, Eunggu Yun, Giung Nam, Edwin Fong, Juho Lee
Martingale Posterior Neural Processes. ICLR (2023)
Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
Self-Supervised Dataset Distillation for Transfer Learning. CoRR (2023)
Jeffrey Willette, Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation. ICML (2023)
Hyunsu Kim, Hyungi Lee, Hongseok Yang, Juho Lee
Regularizing Towards Soft Equivariance Under Mixed Symmetries. CoRR (2023)
Francois Caron, Fadhel Ayed, Paul Jung, Hoil Lee, Juho Lee, Hongseok Yang
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning. CoRR (2023)
Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
Set-based Meta-Interpolation for Few-Task Meta-Learning. NeurIPS (2022)
Jeffrey Willette, Andreis Bruno, Juho Lee, Sung Ju Hwang
Universal Mini-Batch Consistency for Set Encoding Functions. CoRR (2022)
Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, François Caron
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility. CoRR (2022)
Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha, Juho Lee
On Divergence Measures for Bayesian Pseudocoresets. CoRR (2022)
Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi
Self-Distillation for Further Pre-training of Transformers. CoRR (2022)
Bruno Andreis, Seanie Lee, Tuan A. Nguyen, Juho Lee, Eunho Yang, Sung Ju Hwang
Set Based Stochastic Subsampling. ICML (2022)
Seanie Lee, Haebeom Lee, Juho Lee, Sung Ju Hwang
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning. ICLR (2022)
Giung Nam, Hyungi Lee, Byeongho Heo, Juho Lee
Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation. CoRR (2022)
Jeffrey Ryan Willette, Hae Beom Lee, Juho Lee, Sung Ju Hwang
Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty. ICLR (2022)
Seanie Lee, Andreis Bruno, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
Set-based Meta-Interpolation for Few-Task Meta-Learning. CoRR (2022)
Youngwan Lee, Jeffrey Willette, Jonghee Kim, Juho Lee, Sung Ju Hwang
Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders. CoRR (2022)
Giung Nam, Hyungi Lee, Byeongho Heo, Juho Lee
Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation. ICML (2022)
Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha, Juho Lee
On Divergence Measures for Bayesian Pseudocoresets. NeurIPS (2022)
Hyungi Lee, Eunggu Yun, Hongseok Yang, Juho Lee
Scale Mixtures of Neural Network Gaussian Processes. ICLR (2022)
Yanbin Liu, Juho Lee, Linchao Zhu, Ling Chen, Humphrey Shi, Yi Yang
A Multi-Mode Modulator for Multi-Domain Few-Shot Classification. ICCV (2021)
Andreis Bruno, Jeffrey Willette, Juho Lee, Sung Ju Hwang
Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding. NeurIPS (2021)
Giung Nam, Jongmin Yoon, Yoonho Lee, Juho Lee
Diversity Matters When Learning From Ensembles. NeurIPS (2021)