Ross Goroshin
I am currently a Research Scientist in the Google Brain Montreal team. My main area of expertise is Deep Learning. I'm mainly interested in building flexible and robust computer vision systems by applying ideas from self-supervised and meta-learning.
Prior to joining the Brain team I was at DeepMind (London UK) where I worked on navigation problems using reinforcement learning. I completed by PhD under the supervision of Yann LeCun at NYU.
Research Areas
Authored Publications
Sort By
Google
Satellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping
Alex Wilson
Betty Peng
Carl Elkin
Umangi Jain
2024
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
Jesse Farebrother
Joshua Greaves
Charline Le Lan
Marc Bellemare
International Conference on Learning Representations (ICLR) (2023)
Impact of Aliasing on Generalization in Deep Convolutional Networks
Nicolas Le Roux
Rob Romijnders
International Conference on Computer Vision ICCV 2021, IEEE/CVF (2021)
A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches
Neil Houlsby
Xiaohua Zhai
Sylvain Gelly
NeurIPS Datasets and Benchmarks Track (2021)
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Eleni Triantafillou
Tyler Zhu
Kelvin Xu
Carles Gelada
International Conference on Learning Representations (submission) (2020)
Vector-based Navigation using Grid-like Representations in Artificial Agents.
Alexander Pritzel
Andrea Banino
Benigno Uria
Brian C Zhang
Caswell Barry
Charles Blundell
Charlie Beattie
Demis Hassabis
Dharshan Kumaran
Greg Wayne
Helen King
Hubert Soyer
Joseph Modayil
Koray Kavukcuoglu
Martin J. Chadwick
Neil Rabinowitz
Raia Hadsell
Razvan Pascanu
Stephen Gaffney
Stig Vilholm Petersen
Thomas Degris
Timothy Lillicrap
Nature (2018)
