Ivo Danihelka

According to our database, Ivo Danihelka authored at least 22 papers between 2009 and 2023.

Collaborative distances:

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

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

Learning by Directional Gradient Descent.

David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt

Proceedings of the Tenth International Conference on Learning Representations, 2022

Policy improvement by planning with Gumbel.

Ivo Danihelka, Arthur Guez, Julian Schrittwieser, David Silver

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Muesli: Combining Improvements in Policy Optimization.

Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Causally Correct Partial Models for Reinforcement Learning.

Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing

CoRR, 2020

2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.

Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver

Nat., 2019

OpenSpiel: A Framework for Reinforcement Learning in Games.

Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinícius Flores Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas W. Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis

CoRR, 2019

2017

Comparison of Maximum Likelihood and GAN-based training of Real NVPs.

Ivo Danihelka, Balaji Lakshminarayanan, Benigno Uria, Daan Wierstra, Peter Dayan

CoRR, 2017

The Cramer Distance as a Solution to Biased Wasserstein Gradients.

Marc G. Bellemare, Ivo Danihelka, Will Dabney, Shakir Mohamed, Balaji Lakshminarayanan, Stephan Hoyer, Rémi Munos

CoRR, 2017

Video Pixel Networks.

Nal Kalchbrenner, Aäron van den Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, Koray Kavukcuoglu

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Hybrid computing using a neural network with dynamic external memory.

Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwinska, Sergio Gomez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John P. Agapiou, Adrià Puigdomènech Badia, Karl Moritz Hermann, Yori Zwols, Georg Ostrovski, Adam Cain, Helen King, Christopher Summerfield, Phil Blunsom, Koray Kavukcuoglu, Demis Hassabis

Nat., 2016

Grid Long Short-Term Memory.

Nal Kalchbrenner, Ivo Danihelka, Alex Graves

Proceedings of the 4th International Conference on Learning Representations, 2016

Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes.

Jack W. Rae, Jonathan J. Hunt, Ivo Danihelka, Timothy Harley, Andrew W. Senior, Gregory Wayne, Alex Graves, Tim Lillicrap

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Memory-Efficient Backpropagation Through Time.

Audrunas Gruslys, Rémi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Towards Conceptual Compression.

Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

One-Shot Generalization in Deep Generative Models.

Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra

Proceedings of the 33nd International Conference on Machine Learning, 2016

Associative Long Short-Term Memory.

Ivo Danihelka, Greg Wayne, Benigno Uria, Nal Kalchbrenner, Alex Graves

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

DRAW: A Recurrent Neural Network For Image Generation.

Karol Gregor, Ivo Danihelka, Alex Graves, Daan Wierstra

CoRR, 2015

DRAW: A Recurrent Neural Network For Image Generation.

Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Neural Turing Machines.

Alex Graves, Greg Wayne, Ivo Danihelka

CoRR, 2014

Deep AutoRegressive Networks.

Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

Proceedings of the 31th International Conference on Machine Learning, 2014

2009

Optimistic Simulated Exploration as an Incentive for Real Exploration

Ivo Danihelka

CoRR, 2009