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Timur Garipov
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2020 – today
- 2024
- [i11]Anna Glazkova, Dmitry Morozov, Timur Garipov:
Key Algorithms for Keyphrase Generation: Instruction-Based LLMs for Russian Scientific Keyphrases. CoRR abs/2410.18040 (2024) - 2023
- [c7]Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola:
Compositional Sculpting of Iterative Generative Processes. NeurIPS 2023 - [i10]Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola:
Compositional Sculpting of Iterative Generative Processes. CoRR abs/2309.16115 (2023) - 2022
- [c6]Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola:
Adversarial Support Alignment. ICLR 2022 - [i9]Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola:
Adversarial Support Alignment. CoRR abs/2203.08908 (2022) - 2020
- [i8]Shangyuan Tong, Timur Garipov, Tommi S. Jaakkola:
The Benefits of Pairwise Discriminators for Adversarial Training. CoRR abs/2002.08621 (2020)
2010 – 2019
- 2019
- [c5]Wesley J. Maddox, Pavel Izmailov, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson:
A Simple Baseline for Bayesian Uncertainty in Deep Learning. NeurIPS 2019: 13132-13143 - [c4]Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson:
Subspace Inference for Bayesian Deep Learning. UAI 2019: 1169-1179 - [i7]Wesley J. Maddox, Timur Garipov, Pavel Izmailov, Dmitry P. Vetrov, Andrew Gordon Wilson:
A Simple Baseline for Bayesian Uncertainty in Deep Learning. CoRR abs/1902.02476 (2019) - [i6]Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson:
Subspace Inference for Bayesian Deep Learning. CoRR abs/1907.07504 (2019) - [i5]Diego Granziol, Xingchen Wan, Timur Garipov, Dmitry P. Vetrov, Stephen Roberts:
MLRG Deep Curvature. CoRR abs/1912.09656 (2019) - 2018
- [c3]Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Bayesian Incremental Learning for Deep Neural Networks. ICLR (Workshop) 2018 - [c2]Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P. Vetrov, Andrew Gordon Wilson:
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs. NeurIPS 2018: 8803-8812 - [c1]Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson:
Averaging Weights Leads to Wider Optima and Better Generalization. UAI 2018: 876-885 - [i4]Max Kochurov, Timur Garipov, Dmitry Podoprikhin, Dmitry Molchanov, Arsenii Ashukha, Dmitry P. Vetrov:
Bayesian Incremental Learning for Deep Neural Networks. CoRR abs/1802.07329 (2018) - [i3]Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P. Vetrov, Andrew Gordon Wilson:
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs. CoRR abs/1802.10026 (2018) - [i2]Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson:
Averaging Weights Leads to Wider Optima and Better Generalization. CoRR abs/1803.05407 (2018) - 2016
- [i1]Timur Garipov, Dmitry Podoprikhin, Alexander Novikov, Dmitry P. Vetrov:
Ultimate tensorization: compressing convolutional and FC layers alike. CoRR abs/1611.03214 (2016)
Coauthor Index
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