Scholar
Andrei Atanov
Google Scholar ID: XriU_R8AAAAJ
EPFL
Citations & Impact
Citations
719
H-index
6
i10-index
6
Publications
17
Co-authors
7
list available
Publications
Resume (English only)
Academic Achievements
- 1. 'How far can a 1-pixel camera go?', ECCV, 2024
- 2. 'Controlled Training Data Generation with Diffusion Models', Arxiv, 2024
- 3. 'Computational Design of Diverse Morphologies and Sensors for Vision and Robotics', CVPR Tutorial, 2024
- 4. 'Unraveling the Key Components of OOD Generalization via Diversification', ICLR, 2024
- 5. 'Task Discovery: Finding the Tasks that Neural Networks Generalize on', NeurIPS, 2022
- 6. 'Multimae: Multi-modal multi-task masked autoencoders', ECCV, 2022
- 7. '3D Common Corruptions and Data Augmentation', CVPR, 2022 (Oral)
- 8. 'The Deep Weight Prior', ICLR, 2019
- 9. 'Semi-Conditional Normalizing Flows for Semi-Supervised Learning', INNF Workshop at ICML, 2019
Research Experience
- PhD student at VILAB (EPFL); Junior researcher at BayesGroup and Samsung-HSE Lab.
Education
- PhD student at EPFL, supervised by Amir Zamir; Bachelor's and Master's degrees in Computer Science from HSE University, supervised by Dmitry Vetrov.
Background
- Research interests: Building deep learning systems that can perceive, understand, and act in the world. Previously a junior researcher at BayesGroup and Samsung-HSE Lab.
Miscellany
- Contact: Email, CV, Google Scholar, GitHub, Twitter
