Timur Garipov

According to our database, Timur Garipov authored at least 10 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Compositional Sculpting of Iterative Generative Processes.

Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas K. Garg, Samuel Kaski, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Adversarial Support Alignment.

Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

The Benefits of Pairwise Discriminators for Adversarial Training.

Shangyuan Tong, Timur Garipov, Tommi S. Jaakkola

CoRR, 2020

2019

MLRG Deep Curvature.

Diego Granziol, Xingchen Wan, Timur Garipov, Dmitry P. Vetrov, Stephen Roberts

CoRR, 2019

Subspace Inference for Bayesian Deep Learning.

Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

A Simple Baseline for Bayesian Uncertainty in Deep Learning.

Wesley J. Maddox, Pavel Izmailov, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Averaging Weights Leads to Wider Optima and Better Generalization.

Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs.

Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P. Vetrov, Andrew Gordon Wilson

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Bayesian Incremental Learning for Deep Neural Networks.

Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov

Proceedings of the 6th International Conference on Learning Representations, 2018

2016

Ultimate tensorization: compressing convolutional and FC layers alike.

Timur Garipov, Dmitry Podoprikhin, Alexander Novikov, Dmitry P. Vetrov

CoRR, 2016