Anna Kuzina

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 17

Top Topics

Convolution Kernel

Generative Model

Knowledge Transfer

Top Venues

Publications

Haotian Chen, Anna Kuzina, Babak Esmaeili, Jakub M. Tomczak
Variational Stochastic Gradient Descent for Deep Neural Networks. CoRR (2024)
Anna Kuzina, Jakub M. Tomczak
Analyzing the Posterior Collapse in Hierarchical Variational Autoencoders. CoRR (2023)
Michal Zajac, Kamil Deja, Anna Kuzina, Jakub M. Tomczak, Tomasz Trzcinski, Florian Shkurti, Piotr Milos
Exploring Continual Learning of Diffusion Models. CoRR (2023)
Anna Kuzina, Kumar Pratik, Fabio Valerio Massoli, Arash Behboodi
Equivariant Priors for Compressed Sensing with Unknown Orientation. CoRR (2022)
David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn
CKConv: Continuous Kernel Convolution For Sequential Data. ICLR (2022)
Anna Kuzina, Max Welling, Jakub M. Tomczak
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC. NeurIPS (2022)
Anna Kuzina, Kumar Pratik, Fabio Valerio Massoli, Arash Behboodi
Equivariant Priors for compressed sensing with unknown orientation. ICML (2022)
Anna Kuzina, Max Welling, Jakub M. Tomczak
Defending Variational Autoencoders from Adversarial Attacks with MCMC. CoRR (2022)
Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. NeurIPS (2022)
Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. CoRR (2022)
Anna Kuzina, Max Welling, Jakub M. Tomczak
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks. CoRR (2021)
David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
CKConv: Continuous Kernel Convolution For Sequential Data. CoRR (2021)
Evgenii Egorov, Anna Kuzina, Evgeny Burnaev
BooVAE: Boosting Approach for Continual Learning of VAE. NeurIPS (2021)
Anna Kuzina, Evgenii Egorov, Evgeny Burnaev
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems. CoRR (2019)
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 (2019)
Anna Kuzina, Evgenii Egorov, Evgeny Burnaev
BooVAE: A scalable framework for continual VAE learning under boosting approach. CoRR (2019)
Marina Pominova, Anna Kuzina, Ekaterina Kondrateva, Svetlana Sushchinskaya, Evgeny Burnaev, Vyacheslav Yarkin, Maxim Sharaev
Ensemble of 3D CNN Regressors with Data Fusion for Fluid Intelligence Prediction. ABCD-NP@MICCAI (2019)