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ORCIDAndrei Atanov
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2020 – today
- 2024
[c8]Andrei Atanov, Jiawei Fu, Rishubh Singh, Isabella Yu, Andrew Spielberg, Amir Zamir:
How Far Can a 1-Pixel Camera Go? Solving Vision Tasks Using Photoreceptors and Computationally Designed Visual Morphology. ECCV (74) 2024: 458-476- [c7]Harold Benoit, Liangze Jiang, Andrei Atanov, Oguzhan Fatih Kar, Mattia Rigotti, Amir Zamir:
Unraveling the Key Components of OOD Generalization via Diversification. ICLR 2024 - [i11]Teresa Yeo, Andrei Atanov, Harold Benoit, Aleksandr Alekseev, Ruchira Ray, Pooya Esmaeil Akhoondi, Amir Zamir:
Controlled Training Data Generation with Diffusion Models. CoRR abs/2403.15309 (2024) - [i10]Andrei Atanov, Jiawei Fu, Rishubh Singh, Isabella Yu, Andrew Spielberg, Amir Zamir:
Solving Vision Tasks with Simple Photoreceptors Instead of Cameras. CoRR abs/2406.11769 (2024) - 2023
- [i9]Harold Benoit, Liangze Jiang, Andrei Atanov, Oguzhan Fatih Kar
, Mattia Rigotti, Amir Zamir:
Unraveling the Key Components of OOD Generalization via Diversification. CoRR abs/2312.16313 (2023) - 2022
- [c6]Oguzhan Fatih Kar, Teresa Yeo, Andrei Atanov, Amir Zamir:
3D Common Corruptions and Data Augmentation. CVPR 2022: 18941-18952 - [c5]Roman Bachmann, David Mizrahi, Andrei Atanov, Amir Zamir:
MultiMAE: Multi-modal Multi-task Masked Autoencoders. ECCV (37) 2022: 348-367 - [c4]Andrei Atanov, Andrei Filatov, Teresa Yeo, Ajay Sohmshetty, Amir Zamir:
Task Discovery: Finding the Tasks that Neural Networks Generalize on. NeurIPS 2022 - [i8]Andrei Atanov, Shijian Xu, Onur Beker, Andrei Filatov, Amir Zamir:
Simple Control Baselines for Evaluating Transfer Learning. CoRR abs/2202.03365 (2022) - [i7]Oguzhan Fatih Kar, Teresa Yeo, Andrei Atanov, Amir Zamir:
3D Common Corruptions and Data Augmentation. CoRR abs/2203.01441 (2022) - [i6]Roman Bachmann, David Mizrahi, Andrei Atanov, Amir Zamir:
MultiMAE: Multi-modal Multi-task Masked Autoencoders. CoRR abs/2204.01678 (2022) - [i5]Andrei Atanov, Andrei Filatov, Teresa Yeo, Ajay Sohmshetty, Amir Zamir:
Task Discovery: Finding the Tasks that Neural Networks Generalize on. CoRR abs/2212.00261 (2022) - 2021
- [i4]Arsenii Ashukha, Andrei Atanov, Dmitry P. Vetrov:
Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations. CoRR abs/2106.08038 (2021)
2010 – 2019
- 2019
- [c3]Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling:
The Deep Weight Prior. ICLR (Poster) 2019 - [c2]Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov:
Uncertainty Estimation via Stochastic Batch Normalization. ISNN (1) 2019: 261-269 - [i3]Andrei Atanov, Alexandra Volokhova, Arsenii Ashukha, Ivan Sosnovik, Dmitry P. Vetrov:
Semi-Conditional Normalizing Flows for Semi-Supervised Learning. CoRR abs/1905.00505 (2019) - 2018
- [c1]Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov:
Uncertainty Estimation via Stochastic Batch Normalization. ICLR (Workshop) 2018 - [i2]Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov:
Uncertainty Estimation via Stochastic Batch Normalization. CoRR abs/1802.04893 (2018) - [i1]Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling:
The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models. CoRR abs/1810.06943 (2018)
Coauthor Index
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