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Jaehoon Lee
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Year
Deep Neural Networks as Gaussian Processes
J Lee*, Y Bahri*, R Novak, SS Schoenholz, J Pennington, ...
International Conference on Learning Representations (ICLR), 2018
12082018
Wide neural networks of any depth evolve as linear models under gradient descent
J Lee*, L Xiao*, SS Schoenholz, Y Bahri, J Sohl-Dickstein, J Pennington
Neural Information Processing Systems (NeurIPS), 2019
10302019
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
TMLR 2023, 2022
8192022
Measuring the effects of data parallelism on neural network training
CJ Shallue*, J Lee*, J Antognini, J Sohl-Dickstein, R Frostig, GE Dahl
Journal of Machine Learning Research (2019) 20, 1-49, 2019
4232019
Bayesian Deep Convolutional Neural Networks with Many Channels are Gaussian Processes
R Novak*, L Xiao*, J Lee, Y Bahri, G Yang, D Abolafia, J Pennington, ...
International Conference on Learning Representations (ICLR), 2019
352*2019
On empirical comparisons of optimizers for deep learning
D Choi, CJ Shallue, Z Nado, J Lee, CJ Maddison, GE Dahl
arXiv preprint arXiv:1910.05446, 2019
3382019
Neural tangents: Fast and easy infinite neural networks in python
R Novak*, L Xiao*, J Hron, J Lee, AA Alemi, J Sohl-Dickstein, ...
International Conference on Learning Representations (ICLR), Spotlight, 2020
2422020
Dataset Distillation with Infinitely Wide Convolutional Networks
T Nguyen, R Novak, L Xiao, J Lee
Neural Information Processing Systems (NeurIPS), 2021
1962021
Dataset Meta-Learning from Kernel Ridge-Regression
T Nguyen, Z Chen, J Lee
International Conference on Learning Representations (ICLR), 2021
1882021
Finite versus infinite neural networks: an empirical study
J Lee, SS Schoenholz, J Pennington, B Adlam, L Xiao, R Novak, ...
Neural Information Processing Systems (NeurIPS), Spotlight, 2020
1872020
The superconformal bootstrap in three dimensions
SM Chester, J Lee, SS Pufu, R Yacoby
Journal of High Energy Physics 2014 (9), 1-59, 2014
1682014
Exact correlators of BPS operators from the 3d superconformal bootstrap
SM Chester, J Lee, SS Pufu, R Yacoby
Journal of High Energy Physics 2015 (3), 1-55, 2015
1502015
Explaining neural scaling laws
Y Bahri*, E Dyer*, J Kaplan*, J Lee*, U Sharma*
arXiv preprint arXiv:2102.06701, 2021
1472021
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
702024
On the infinite width limit of neural networks with a standard parameterization
J Sohl-Dickstein, R Novak, SS Schoenholz, J Lee
arXiv preprint arXiv:2001.07301, 2020
502020
Towards NNGP-guided Neural Architecture Search
DS Park*, J Lee*, D Peng, Y Cao, J Sohl-Dickstein
arXiv preprint arXiv:2011.06006, 2020
342020
3d minimal SCFTs from wrapped M5-branes
JB Bae, D Gang, J Lee
Journal of High Energy Physics 2017 (8), 118, 2017
322017
Algebra of Majorana doubling
J Lee, F Wilczek
Physical Review Letters 111 (22), 226402, 2013
322013
Beyond human data: Scaling self-training for problem-solving with language models
A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, PJ Liu, J Harrison, ...
arXiv preprint arXiv:2312.06585, 2023
312023
GLSMs for non-Kähler geometries
A Adams, E Dyer, J Lee
Journal of High Energy Physics 2013 (1), 1-39, 2013
312013
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Articles 1–20