Anna Kuzina

22 papers A* 5Journal 16Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Efficient Reasoning on the Edge.
CoRR
Yelysei Bondarenko, Thomas Hehn, Rob Hesselink, Romain Lepert, Fabio Valerio Massoli, Evgeny Mironov, Leyla Mirvakhabova, Tribhuvanesh Orekondy, Spyridon Stasis, Andrey Kuzmin, Anna Kuzina, Markus Nagel, Ankita Nayak, Corrado Rainone, Ork de Rooij, Paul N. Whatmough, Arash Behboodi, Babak Ehteshami Bejnordi
2025 J jnl
KaVa: Latent Reasoning via Compressed KV-Cache Distillation.
CoRR
Anna Kuzina, Maciej Pioro, Paul N. Whatmough, Babak Ehteshami Bejnordi
2025 J jnl
Variational Stochastic Gradient Descent for Deep Neural Networks.
Trans. Mach. Learn. Res.
Anna Kuzina, Haotian Chen, Babak Esmaeili, Jakub M. Tomczak
2024 J jnl
Hierarchical VAE with a Diffusion-based VampPrior.
CoRR
Anna Kuzina, Jakub M. Tomczak
2024 J jnl
Hierarchical VAE with a Diffusion-based VampPrior.
Trans. Mach. Learn. Res.
Anna Kuzina, Jakub M. Tomczak
2024 J jnl
Variational Stochastic Gradient Descent for Deep Neural Networks.
CoRR
Haotian Chen, Anna Kuzina, Babak Esmaeili, Jakub M. Tomczak
2023 J jnl
Analyzing the Posterior Collapse in Hierarchical Variational Autoencoders.
CoRR
Anna Kuzina, Jakub M. Tomczak
2023 J jnl
Exploring Continual Learning of Diffusion Models.
CoRR
Michal Zajac, Kamil Deja, Anna Kuzina, Jakub M. Tomczak, Tomasz Trzcinski, Florian Shkurti, Piotr Milos
2022 A* conf
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC.
NeurIPS
Anna Kuzina, Max Welling, Jakub M. Tomczak
2022 A* conf
CKConv: Continuous Kernel Convolution For Sequential Data.
ICLR
David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn
2022 J jnl
Defending Variational Autoencoders from Adversarial Attacks with MCMC.
CoRR
Anna Kuzina, Max Welling, Jakub M. Tomczak
2022 J jnl
Equivariant Priors for Compressed Sensing with Unknown Orientation.
CoRR
Anna Kuzina, Kumar Pratik, Fabio Valerio Massoli, Arash Behboodi
2022 A* conf
Equivariant Priors for compressed sensing with unknown orientation.
ICML
Anna Kuzina, Kumar Pratik, Fabio Valerio Massoli, Arash Behboodi
2022 A* conf
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models.
NeurIPS
Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak
2022 J jnl
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models.
CoRR
Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak
2021 A* conf
BooVAE: Boosting Approach for Continual Learning of VAE.
NeurIPS
Evgenii Egorov, Anna Kuzina, Evgeny Burnaev
2021 J jnl
CKConv: Continuous Kernel Convolution For Sequential Data.
CoRR
David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2021 J jnl
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks.
CoRR
Anna Kuzina, Max Welling, Jakub M. Tomczak
2019 J jnl
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems.
CoRR
Anna Kuzina, Evgenii Egorov, Evgeny Burnaev
2019 J jnl
BooVAE: A scalable framework for continual VAE learning under boosting approach.
CoRR
Anna Kuzina, Evgenii Egorov, Evgeny Burnaev
2019 — conf
Ensemble of 3D CNN Regressors with Data Fusion for Fluid Intelligence Prediction.
ABCD-NP@MICCAI
Marina Pominova, Anna Kuzina, Ekaterina Kondrateva, Svetlana Sushchinskaya, Evgeny Burnaev, Vyacheslav Yarkin, Maxim Sharaev
2019 J jnl
Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction.
CoRR
Marina Pominova, Anna Kuzina, Ekaterina Kondrateva, Svetlana Sushchinskaya, Maxim Sharaev, Evgeny Burnaev, Vyacheslav Yarkin