Juhan Bae - RankMe

40 papers A* 11B 2C 1Journal 23Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Gauss-Newton Unlearning for the LLM Era. CoRR Lev McKinney, Anvith Thudi, Juhan Bae, Tara Rezaei, Nicolas Papernot, Sheila A. McIlraith, Roger B. Grosse
2025	J	`jnl`	Accelerating Neural Network Training: An Analysis of the AlgoPerf Competition. CoRR Priya Kasimbeg, Frank Schneider, Runa Eschenhagen, Juhan Bae, Chandramouli Shama Sastry, Mark Saroufim, Boyuan Feng, Less Wright, Edward Z. Yang, Zachary Nado, Sourabh Medapati, Philipp Hennig, Michael Rabbat, George E. Dahl
2025	A*	`conf`	Accelerating neural network training: An analysis of the AlgoPerf competition. ICLR Priya Kasimbeg, Frank Schneider, Runa Eschenhagen, Juhan Bae, Chandramouli Shama Sastry, Mark Saroufim, Boyuan Feng, Less Wright, Edward Z. Yang, Zachary Nado, Sourabh Medapati, Philipp Hennig, Michael Rabbat, George E. Dahl
2025	J	`jnl`	Better Training Data Attribution via Better Inverse Hessian-Vector Products. CoRR Andrew Wang, Elisa Nguyen, Runshi Yang, Juhan Bae, Sheila A. McIlraith, Roger B. Grosse
2025	J	`jnl`	Exploring Training Data Attribution under Limited Access Constraints. CoRR Shiyuan Zhang, Junwei Deng, Juhan Bae, Jiaqi Ma
2025	J	`jnl`	IF-GUIDE: Influence Function-Guided Detoxification of LLMs. CoRR Zachary Coalson, Juhan Bae, Nicholas Carlini, Sanghyun Hong
2025	A*	`conf`	Influence Functions for Scalable Data Attribution in Diffusion Models. ICLR Bruno Kacper Mlodozeniec, Runa Eschenhagen, Juhan Bae, Alexander Immer, David Krueger, Richard E. Turner
2025	A*	`conf`	Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. ICLR Laura Ruis, Maximilian Mozes, Juhan Bae, Siddhartha Rao Kamalakara, Dwaraknath Gnaneshwar, Acyr Locatelli, Robert Kirk, Tim Rocktäschel, Edward Grefenstette, Max Bartolo
2025	J	`jnl`	Spectral-factorized Positive-definite Curvature Learning for NN Training. CoRR Wu Lin, Felix Dangel, Runa Eschenhagen, Juhan Bae, Richard E. Turner, Roger B. Grosse
2025	J	`jnl`	Training Data Attribution (TDA): Examining Its Adoption & Use Cases. CoRR Deric Cheng, Juhan Bae, Justin Bullock, David Kristofferson
2024	A*	`conf`	Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective. ICML Wu Lin, Felix Dangel, Runa Eschenhagen, Juhan Bae, Richard E. Turner, Alireza Makhzani
2024	J	`jnl`	Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective. CoRR Wu Lin, Felix Dangel, Runa Eschenhagen, Juhan Bae, Richard E. Turner, Alireza Makhzani
2024	J	`jnl`	Influence Functions for Scalable Data Attribution in Diffusion Models. CoRR Bruno Mlodozeniec, Runa Eschenhagen, Juhan Bae, Alexander Immer, David Krueger, Richard E. Turner
2024	J	`jnl`	Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. CoRR Laura Ruis, Maximilian Mozes, Juhan Bae, Siddhartha Rao Kamalakara, Dwarak Talupuru, Acyr Locatelli, Robert Kirk, Tim Rocktäschel, Edward Grefenstette, Max Bartolo
2024	J	`jnl`	Training Data Attribution via Approximate Unrolled Differentiation. CoRR Juhan Bae, Wu Lin, Jonathan Lorraine, Roger B. Grosse
2024	A*	`conf`	Training Data Attribution via Approximate Unrolling. NeurIPS Juhan Bae, Wu Lin, Jonathan Lorraine, Roger B. Grosse
2024	J	`jnl`	What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions. CoRR 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, Roger B. Grosse, Eric P. Xing
2023	J	`jnl`	Benchmarking Neural Network Training Algorithms. CoRR George E. Dahl, Frank Schneider, Zachary Nado, Naman Agarwal, Chandramouli Shama Sastry, Philipp Hennig, Sourabh Medapati, Runa Eschenhagen, Priya Kasimbeg, Daniel Suo, Juhan Bae, Justin Gilmer, Abel L. Peirson, Bilal Khan, Rohan Anil, Mike Rabbat, Shankar Krishnan, Daniel Snider, Ehsan Amid, Kongtao Chen, Chris J. Maddison, Rakshith Vasudev, Michal Badura, Ankush Garg, Peter Mattson
2023	A*	`conf`	Efficient Parametric Approximations of Neural Network Function Space Distance. ICML Nikita Dhawan, Sicong Huang, Juhan Bae, Roger Baker Grosse
2023	J	`jnl`	Efficient Parametric Approximations of Neural Network Function Space Distance. CoRR Nikita Dhawan, Sicong Huang, Juhan Bae, Roger B. Grosse
2023	A*	`conf`	Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. ICLR Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Baker Grosse
2023	J	`jnl`	Studying Large Language Model Generalization with Influence Functions. CoRR 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, Karina Nguyen, Nicholas Joseph, Sam McCandlish, Jared Kaplan, Samuel R. Bowman
2023	J	`jnl`	Using Large Language Models for Hyperparameter Optimization. CoRR Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba
2022	A*	`conf`	Amortized Proximal Optimization. NeurIPS Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse
2022	J	`jnl`	Amortized Proximal Optimization. CoRR Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse
2022	A*	`conf`	If Influence Functions are the Answer, Then What is the Question? NeurIPS Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse
2022	J	`jnl`	If Influence Functions are the Answer, Then What is the Question? CoRR Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse
2022	J	`jnl`	Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. CoRR Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger B. Grosse
2021	J	`jnl`	Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes. CoRR James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse
2021	A*	`conf`	On Monotonic Linear Interpolation of Neural Network Parameters. ICML James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse
2020	A*	`conf`	Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians. NeurIPS Juhan Bae, Roger B. Grosse
2020	J	`jnl`	Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians. CoRR Juhan Bae, Roger B. Grosse
2019	B	`conf`	Fast 6DOF Pose Estimation with Synthetic Textureless CAD Model for Mobile Applications. ICIP Bowen Chen, Juhan Bae, Dibyendu Mukherjee
2018	J	`jnl`	Eigenvalue Corrected Noisy Natural Gradient. CoRR Juhan Bae, Guodong Zhang, Roger B. Grosse
2018	—	`conf`	Learnable Pooling Methods for Video Classification. ECCV Workshops (4) Sebastian Kmiec, Juhan Bae, Ruijian An
2018	J	`jnl`	Learnable Pooling Methods for Video Classification. CoRR Sebastian Kmiec, Juhan Bae, Ruijian An
2018	—	`conf`	Study on HDR/WCG Service Model for UHD Service. APSIPA Juhan Bae, Jeongyeon Lim, So-Ki Jung
2015	—	`conf`	Robust visual tracking through deep learning-based confidence evaluation. URAI Euntae Hong, Juhan Bae, Jongwoo Lim
2014	B	`conf`	Semi-online video stabilization using probabilistic keyframe update and inter-keyframe motion smoothing. ICIP Juhan Bae, Youngbae Hwang, Jongwoo Lim
2013	C	`conf`	Background subtraction using edge cues and color difference for stabilized CMOS images. ICCE Juhan Bae, Youngbae Hwang, Byeongho Choi