Follow
Guodong Zhang
Guodong Zhang
xAI
Verified email at x.ai - Homepage
Title
Cited by
Cited by
Year
Deformable convolutional networks
J Dai*, H Qi*, Y Xiong*, Y Li*, G Zhang*, H Hu, Y Wei (* co-first author)
International Conference on Computer Vision, 2017
59052017
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
6222023
Picking Winning Tickets Before Training by Preserving Gradient Flow
C Wang, G Zhang, R Grosse
International Conference on Learning Representations, 2020
5652020
Benchmarking Model-Based Reinforcement Learning
T Wang, X Bao, I Clavera, J Hoang, Y Wen, E Langlois, S Zhang, G Zhang, ...
4152019
Functional Variational Bayesian Neural Networks
S Sun*, G Zhang*, J Shi*, R Grosse (* indicates co-first author)
International Conference on Learning Representations, 2019
2802019
Three Mechanisms of Weight Decay Regularization
G Zhang, C Wang, B Xu, R Grosse
International Conference on Learning Representations, 2019
2642019
Noisy Natural Gradient as Variational Inference
G Zhang*, S Sun*, D Duvenaud, R Grosse (* indicates co-first author)
International Conference on Machine Learning, 2018
2272018
Which algorithmic choices matter at which batch sizes? insights from a noisy quadratic model
G Zhang, L Li, Z Nado, J Martens, S Sachdeva, G Dahl, C Shallue, ...
Advances in neural information processing systems, 2019
1272019
Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks
G Zhang, J Martens, R Grosse
Advances in Neural Information Processing Systems, 2019
1262019
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
Y Wang*, G Zhang*, J Ba (* indicates co-first author)
International Conference on Learning Representations, 2020
1082020
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
C Wang, R Grosse, S Fidler, G Zhang
International Conference on Machine Learning, 2019
1072019
Differentiable Compositional Kernel Learning for Gaussian Processes
S Sun, G Zhang, C Wang, W Zeng, J Li, R Grosse
International Conference on Machine Learning, 2018
872018
An empirical study of stochastic gradient descent with structured covariance noise
Y Wen, K Luk, M Gazeau, G Zhang, H Chan, J Ba
International Conference on Artificial Intelligence and Statistics, 3621-3631, 2020
54*2020
Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization
G Zhang, Y Wang, L Lessard, R Grosse
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
492022
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise
G Zhang, K Hsu, J Li, C Finn, R Grosse
Advances in Neural Information Processing Systems, 2021
292021
Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers
G Zhang, A Botev, J Martens
International Conference on Learning Representations, 2022
282022
A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints
G Zhang, X Bao, L Lessard, R Grosse
Journal of Machine Learning Research, 2021
262021
Eigenvalue Corrected Noisy Natural Gradient
J Bae, G Zhang, R Grosse
Neural Information Processing Systems (Bayesian Deep Learning Workshop), 2018
232018
Deep transformers without shortcuts: Modifying self-attention for faithful signal propagation
B He, J Martens, G Zhang, A Botev, A Brock, SL Smith, YW Teh
arXiv preprint arXiv:2302.10322, 2023
182023
On the suboptimality of negative momentum for minimax optimization
G Zhang, Y Wang
International Conference on Artificial Intelligence and Statistics, 2021
182021
The system can't perform the operation now. Try again later.
Articles 1–20