Nikolay Savinov

According to our database, Nikolay Savinov authored at least 18 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy P. Lillicrap, Jean-Baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, Ioannis Antonoglou, Rohan Anil, Sebastian Borgeaud, Andrew M. Dai, Katie Millican, Ethan Dyer, Mia Glaese, Thibault Sottiaux, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, James Molloy, Jilin Chen, Michael Isard, Paul Barham, Tom Hennigan, Ross McIlroy, Melvin Johnson, Johan Schalkwyk, Eli Collins, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, Clemens Meyer, Gregory Thornton, Zhen Yang, Henryk Michalewski, Zaheer Abbas, Nathan Schucher, Ankesh Anand, Richard Ives, James Keeling, Karel Lenc, Salem Haykal, Siamak Shakeri, Pranav Shyam, Aakanksha Chowdhery, Roman Ring, Stephen Spencer, Eren Sezener, et al.

CoRR, 2024

2023

Gemini: A Family of Highly Capable Multimodal Models.

Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M. Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy P. Lillicrap, Angeliki Lazaridou, Orhan Firat, James Molloy, Michael Isard, Paul Ronald Barham, Tom Hennigan, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, Ryan Doherty, Eli Collins, Clemens Meyer, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, George Tucker, Enrique Piqueras, Maxim Krikun, Iain Barr, Nikolay Savinov, Ivo Danihelka, Becca Roelofs, Anaïs White, Anders Andreassen, Tamara von Glehn, Lakshman Yagati, Mehran Kazemi, Lucas Gonzalez, Misha Khalman, Jakub Sygnowski, et al.

CoRR, 2023

2022

Continuous diffusion for categorical data.

Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler

CoRR, 2022

Self-conditioned Embedding Diffusion for Text Generation.

Robin Strudel, Corentin Tallec, Florent Altché, Yilun Du, Yaroslav Ganin, Arthur Mensch, Will Grathwohl, Nikolay Savinov, Sander Dieleman, Laurent Sifre, Rémi Leblond

CoRR, 2022

Step-unrolled Denoising Autoencoders for Text Generation.

Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, Aäron van den Oord

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

Imitating Interactive Intelligence.

Josh Abramson, Arun Ahuja, Arthur Brussee, Federico Carnevale, Mary Cassin, Stephen Clark, Andrew Dudzik, Petko Georgiev, Aurelia Guy, Tim Harley, Felix Hill, Alden Hung, Zachary Kenton, Jessica Landon, Timothy P. Lillicrap, Kory W. Mathewson, Alistair Muldal, Adam Santoro, Nikolay Savinov, Vikrant Varma, Greg Wayne, Nathaniel Wong, Chen Yan, Rui Zhu

CoRR, 2020

2019

Modeling the visual world: reconstruction and neural episodic representation.

Nikolay Savinov

PhD thesis, 2019

RNN-based Generative Model for Fine-Grained Sketching.

Andrin Jenal, Nikolay Savinov, Torsten Sattler, Gaurav Chaurasia

CoRR, 2019

Episodic Curiosity through Reachability.

Nikolay Savinov, Anton Raichuk, Damien Vincent, Raphaël Marinier, Marc Pollefeys, Timothy P. Lillicrap, Sylvain Gelly

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

2018

Semi-parametric topological memory for navigation.

Nikolay Savinov, Alexey Dosovitskiy, Vladlen Koltun

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

Conditional Affordance Learning for Driving in Urban Environments.

Axel Sauer, Nikolay Savinov, Andreas Geiger

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark.

Timo Hackel, Nikolay Savinov, Lubor Ladicky, Jan Dirk Wegner, Konrad Schindler, Marc Pollefeys

CoRR, 2017

Matching neural paths: transfer from recognition to correspondence search.

Nikolay Savinov, Lubor Ladicky, Marc Pollefeys

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Quad-Networks: Unsupervised Learning to Rank for Interest Point Detection.

Nikolay Savinov, Akihito Seki, Lubor Ladicky, Torsten Sattler, Marc Pollefeys

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Semantic 3D Reconstruction with Continuous Regularization and Ray Potentials Using a Visibility Consistency Constraint.

Nikolay Savinov, Christian Häne, Lubor Ladicky, Marc Pollefeys

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

TI-POOLING: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks.

Dmitry Laptev, Nikolay Savinov, Joachim M. Buhmann, Marc Pollefeys

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Discrete optimization of ray potentials for semantic 3D reconstruction.

Nikolay Savinov, Lubor Ladicky, Christian Hane, Marc Pollefeys

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Class Specific 3D Object Shape Priors Using Surface Normals.

Christian Häne, Nikolay Savinov, Marc Pollefeys

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014