Background subtraction using edge cues and color difference for stabilized CMOS images. - Juhan Bae; Youngbae Hwang; Byeongho Choi (ICCE, 2013)

Semi-online video stabilization using probabilistic keyframe update and inter-keyframe motion smoothing. - Juhan Bae; Youngbae Hwang; Jongwoo Lim (ICIP, 2014)

Robust visual tracking through deep learning-based confidence evaluation. - Euntae Hong; Juhan Bae; Jongwoo Lim (URAI, 2015)

Study on HDR/WCG Service Model for UHD Service. - Juhan Bae; Jeongyeon Lim; So-Ki Jung (APSIPA, 2018)

Learnable Pooling Methods for Video Classification. - Sebastian Kmiec; Juhan Bae; Ruijian An (ECCV Workshops (4), 2018)

Eigenvalue Corrected Noisy Natural Gradient. - Juhan Bae; Guodong Zhang 006; Roger B. Grosse (CoRR, 2018)

Fast 6DOF Pose Estimation with Synthetic Textureless CAD Model for Mobile Applications. - Bowen Chen; Juhan Bae; Dibyendu Mukherjee (ICIP, 2019)

Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians. - Juhan Bae; Roger B. Grosse (NeurIPS, 2020)

On Monotonic Linear Interpolation of Neural Network Parameters. - James Lucas; Juhan Bae; Michael R. Zhang; Stanislav Fort; Richard S. Zemel; Roger B. Grosse (ICML, 2021)

Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes. - James Lucas; Juhan Bae; Michael R. Zhang; Stanislav Fort; Richard S. Zemel; Roger B. Grosse (CoRR, 2021)

If Influence Functions are the Answer, Then What is the Question? - Juhan Bae; Nathan Ng 001; Alston Lo; Marzyeh Ghassemi; Roger B. Grosse (NeurIPS, 2022)

Amortized Proximal Optimization. - Juhan Bae; Paul Vicol; Jeff Z. HaoChen; Roger B. Grosse (NeurIPS, 2022)

Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. - Juhan Bae; Michael R. Zhang; Michael Ruan; Eric Wang; So Hasegawa; Jimmy Ba; Roger Baker Grosse (ICLR, 2023)

Efficient Parametric Approximations of Neural Network Function Space Distance. - Nikita Dhawan; Sicong Huang 001; Juhan Bae; Roger Baker Grosse (ICML, 2023)

Benchmarking Neural Network Training Algorithms. - George E. Dahl; Frank Schneider 001; Zachary Nado; Naman Agarwal; Chandramouli Shama Sastry; Philipp Hennig; Sourabh Medapati; Runa Eschenhagen; Priya Kasimbeg; Daniel Suo; Juhan Bae; Justin Gilmer; et al. (CoRR, 2023)

Studying Large Language Model Generalization with Influence Functions. - Roger B. Grosse; Juhan Bae; Cem Anil; Nelson Elhage; Alex Tamkin; Amirhossein Tajdini; Benoit Steiner; Dustin Li; Esin Durmus; Ethan Perez; Evan Hubinger; Kamile Lukosiute; et al. (CoRR, 2023)

Using Large Language Models for Hyperparameter Optimization. - Michael R. Zhang; Nishkrit Desai; Juhan Bae; Jonathan Lorraine; Jimmy Ba (CoRR, 2023)

Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective. - Wu Lin; Felix Dangel; Runa Eschenhagen; Juhan Bae; Richard E. Turner; Alireza Makhzani (ICML, 2024)

Training Data Attribution via Approximate Unrolling. - Juhan Bae; Wu Lin; Jonathan Lorraine; Roger B. Grosse (NeurIPS, 2024)

Training Data Attribution via Approximate Unrolled Differentiation. - Juhan Bae; Wu Lin; Jonathan Lorraine; Roger B. Grosse (CoRR, 2024)

What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions. - Sang Keun Choe; Hwijeen Ahn; Juhan Bae; Kewen Zhao; Minsoo Kang; Youngseog Chung; Adithya Pratapa; Willie Neiswanger; Emma Strubell; Teruko Mitamura; Jeff G. Schneider; Eduard H. Hovy; et al. (CoRR, 2024)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. - Laura Ruis; Maximilian Mozes; Juhan Bae; Siddhartha Rao Kamalakara; Dwarak Talupuru; Acyr Locatelli; Robert Kirk; Tim Rocktäschel; Edward Grefenstette; Max Bartolo (CoRR, 2024)

Accelerating neural network training: An analysis of the AlgoPerf competition. - Priya Kasimbeg; Frank Schneider 001; Runa Eschenhagen; Juhan Bae; Chandramouli Shama Sastry; Mark Saroufim; Boyuan Feng; Less Wright; Edward Z. Yang; Zachary Nado; Sourabh Medapati; Philipp Hennig; et al. (ICLR, 2025)

Influence Functions for Scalable Data Attribution in Diffusion Models. - Bruno Kacper Mlodozeniec; Runa Eschenhagen; Juhan Bae; Alexander Immer; David Krueger 001; Richard E. Turner (ICLR, 2025)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. - Laura Ruis; Maximilian Mozes; Juhan Bae; Siddhartha Rao Kamalakara; Dwaraknath Gnaneshwar; Acyr Locatelli; Robert Kirk; Tim Rocktäschel; Edward Grefenstette; Max Bartolo (ICLR, 2025)

Training Data Attribution (TDA): Examining Its Adoption & Use Cases. - Deric Cheng; Juhan Bae; Justin Bullock; David Kristofferson (CoRR, 2025)

Spectral-factorized Positive-definite Curvature Learning for NN Training. - Wu Lin; Felix Dangel; Runa Eschenhagen; Juhan Bae; Richard E. Turner; Roger B. Grosse (CoRR, 2025)

IF-GUIDE: Influence Function-Guided Detoxification of LLMs. - Zachary Coalson; Juhan Bae; Nicholas Carlini; Sanghyun Hong 001 (CoRR, 2025)

Better Training Data Attribution via Better Inverse Hessian-Vector Products. - Andrew Wang; Elisa Nguyen; Runshi Yang; Juhan Bae; Sheila A. McIlraith; Roger B. Grosse (CoRR, 2025)