Andrei Atanov

According to our database, Andrei Atanov authored at least 13 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Solving Vision Tasks with Simple Photoreceptors Instead of Cameras.

Andrei Atanov, Jiawei Fu, Rishubh Singh, Isabella Yu, Andrew Spielberg, Amir Zamir

CoRR, 2024

Controlled Training Data Generation with Diffusion Models.

Teresa Yeo, Andrei Atanov, Harold Benoit, Aleksandr Alekseev, Ruchira Ray, Pooya Esmaeil Akhoondi, Amir Zamir

CoRR, 2024

Unraveling the Key Components of OOD Generalization via Diversification.

Harold Benoit, Liangze Jiang, Andrei Atanov, Oguzhan Fatih Kar, Mattia Rigotti, Amir Zamir

Proceedings of the Twelfth International Conference on Learning Representations, 2024

How Far Can a 1-Pixel Camera Go? Solving Vision Tasks Using Photoreceptors and Computationally Designed Visual Morphology.

Andrei Atanov, Jiawei Fu, Rishubh Singh, Isabella Yu, Andrew Spielberg, Amir Zamir

Proceedings of the Computer Vision - ECCV 2024, 2024

2022

Simple Control Baselines for Evaluating Transfer Learning.

Andrei Atanov, Shijian Xu, Onur Beker, Andrei Filatov, Amir Zamir

CoRR, 2022

Task Discovery: Finding the Tasks that Neural Networks Generalize on.

Andrei Atanov, Andrei Filatov, Teresa Yeo, Ajay Sohmshetty, Amir Zamir

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

MultiMAE: Multi-modal Multi-task Masked Autoencoders.

Roman Bachmann, David Mizrahi, Andrei Atanov, Amir Zamir

Proceedings of the Computer Vision - ECCV 2022, 2022

3D Common Corruptions and Data Augmentation.

Oguzhan Fatih Kar, Teresa Yeo, Andrei Atanov, Amir Zamir

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations.

Arsenii Ashukha, Andrei Atanov, Dmitry P. Vetrov

CoRR, 2021

2019

Semi-Conditional Normalizing Flows for Semi-Supervised Learning.

Andrei Atanov, Alexandra Volokhova, Arsenii Ashukha, Ivan Sosnovik, Dmitry P. Vetrov

CoRR, 2019

The Deep Weight Prior.

Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models.

Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling

CoRR, 2018

Uncertainty Estimation via Stochastic Batch Normalization.

Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov

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