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Juhan Bae
Juhan Bae
Graduate Student, University of Toronto
Verified email at cs.toronto.edu - Homepage
Title
Cited by
Cited by
Year
Studying Large Language Model Generalization with Influence Functions
R Grosse, J Bae, C Anil, N Elhage, A Tamkin, A Tajdini, B Steiner, D Li, ...
arXiv preprint arXiv:2308.03296, 2023
1142023
If Influence Functions are the Answer, Then What is the Question?
J Bae, N Ng, A Lo, M Ghassemi, RB Grosse
Advances in Neural Information Processing Systems 35, 17953-17967, 2022
952022
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians
J Bae, RB Grosse
Advances in Neural Information Processing Systems 33, 21725-21737, 2020
322020
Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes
J Lucas, J Bae, MR Zhang, S Fort, R Zemel, R Grosse
Neural Information Processing Systems (Optimization for Machine Learning …, 2021
30*2021
Using Large Language Models for Hyperparameter Optimization
MR Zhang, N Desai, J Bae, J Lorraine, J Ba
Neural Information Processing Systems (Foundation Models for Decision Making …, 2023
272023
Eigenvalue Corrected Noisy Natural Gradient
J Bae, G Zhang, R Grosse
Neural Information Processing Systems (Bayesian Deep Learning Workshop), 2018
242018
Benchmarking Neural Network Training Algorithms
GE Dahl, F Schneider, Z Nado, N Agarwal, CS Sastry, P Hennig, ...
arXiv preprint arXiv:2306.07179, 2023
202023
What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions
SK Choe, H Ahn, J Bae, K Zhao, M Kang, Y Chung, A Pratapa, ...
arXiv preprint arXiv:2405.13954, 2024
172024
Amortized Proximal Optimization
J Bae, P Vicol, JZ HaoChen, RB Grosse
Advances in Neural Information Processing Systems 35, 8982-8997, 2022
172022
Learnable Pooling Methods for Video Classification
S Kmiec, J Bae, R An
Proceedings of the European Conference on Computer Vision (ECCV), 2018
152018
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve
J Bae, MR Zhang, M Ruan, E Wang, S Hasegawa, J Ba, R Grosse
International Conference on Learning Representations 11, 2022
142022
On Monotonic Linear Interpolation of Neural Network Parameters
JR Lucas, J Bae, MR Zhang, S Fort, R Zemel, RB Grosse
International Conference on Machine Learning, 7168-7179, 2021
122021
Training Data Attribution via Approximate Unrolling
J Bae, W Lin, J Lorraine, RB Grosse
The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
9*2024
Efficient Parametric Approximations of Neural Network Function Space Distance
N Dhawan, S Huang, J Bae, RB Grosse
International Conference on Machine Learning, 7795-7812, 2023
52023
Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective
W Lin, F Dangel, R Eschenhagen, J Bae, RE Turner, A Makhzani
arXiv preprint arXiv:2402.03496, 2024
4*2024
CSC 311: Introduction to Machine Learning
R Grosse, C Maddison, J Bae, S Pitis
University of Toronto, Fall, 2020
42020
Fast 6DoF Pose Estimation with Synthetic Textureless CAD Model for Mobile Applications
B Chen, J Bae, D Mukherjee
2019 IEEE International Conference on Image Processing (ICIP), 2541-2545, 2019
22019
Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models
L Ruis, M Mozes, J Bae, SR Kamalakara, D Talupuru, A Locatelli, R Kirk, ...
arXiv preprint arXiv:2411.12580, 2024
2024
Influence Functions for Scalable Data Attribution in Diffusion Models
B Mlodozeniec, R Eschenhagen, J Bae, A Immer, D Krueger, R Turner
arXiv preprint arXiv:2410.13850, 2024
2024
Kronfluence: Influence Functions with Eigenvalue-corrected Kronecker-Factored Approximate Curvature
J Bae
https://doi.org/10.5281/zenodo.13131048, 2024
2024
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Articles 1–20