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Anna Kuzina
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2020 – today
- 2024
- [i11]Haotian Chen, Anna Kuzina, Babak Esmaeili, Jakub M. Tomczak:
Variational Stochastic Gradient Descent for Deep Neural Networks. CoRR abs/2404.06549 (2024) - 2023
- [i10]Anna Kuzina, Jakub M. Tomczak
:
Analyzing the Posterior Collapse in Hierarchical Variational Autoencoders. CoRR abs/2302.09976 (2023) - [i9]Michal Zajac, Kamil Deja
Exploring Continual Learning of Diffusion Models. CoRR abs/2303.15342 (2023) - 2022
- [c6]David W. Romero, Anna Kuzina, Erik J. Bekkers
CKConv: Continuous Kernel Convolution For Sequential Data. ICLR 2022 - [c5]Anna Kuzina, Kumar Pratik, Fabio Valerio Massoli, Arash Behboodi:
Equivariant Priors for compressed sensing with unknown orientation. ICML 2022: 11753-11771 - [c4]Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak:
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. NeurIPS 2022 - [c3]Anna Kuzina, Max Welling, Jakub M. Tomczak:
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC. NeurIPS 2022 - [i8]Anna Kuzina, Max Welling, Jakub M. Tomczak:
Defending Variational Autoencoders from Adversarial Attacks with MCMC. CoRR abs/2203.09940 (2022) - [i7]Kamil Deja
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. CoRR abs/2206.00070 (2022) - [i6]Anna Kuzina, Kumar Pratik, Fabio Valerio Massoli, Arash Behboodi:
Equivariant Priors for Compressed Sensing with Unknown Orientation. CoRR abs/2206.14069 (2022) - 2021
- [c2]Evgenii Egorov, Anna Kuzina, Evgeny Burnaev:
BooVAE: Boosting Approach for Continual Learning of VAE. NeurIPS 2021: 17889-17901 - [i5]David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
CKConv: Continuous Kernel Convolution For Sequential Data. CoRR abs/2102.02611 (2021) - [i4]Anna Kuzina, Max Welling, Jakub M. Tomczak:
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks. CoRR abs/2103.06701 (2021)
2010 – 2019
- 2019
- [c1]Marina Pominova, Anna Kuzina, Ekaterina Kondrateva
Ensemble of 3D CNN Regressors with Data Fusion for Fluid Intelligence Prediction. ABCD-NP@MICCAI 2019: 158-166 - [i3]Marina Pominova, Anna Kuzina, Ekaterina Kondrateva, Svetlana Sushchinskaya, Maxim Sharaev, Evgeny Burnaev, Vyacheslav Yarkin:
Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction. CoRR abs/1905.10550 (2019) - [i2]Anna Kuzina, Evgenii Egorov, Evgeny Burnaev:
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems. CoRR abs/1908.05480 (2019) - [i1]Anna Kuzina, Evgenii Egorov, Evgeny Burnaev:
BooVAE: A scalable framework for continual VAE learning under boosting approach. CoRR abs/1908.11853 (2019)
Coauthor Index
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