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Know your audience: specializing grounded language models with the game of Dixit


Jun 16, 2022
Aaditya K. Singh, David Ding, Andrew Saxe, Felix Hill, Andrew K. Lampinen

* 27 pages, 9 figures 

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Perceiver IO: A General Architecture for Structured Inputs & Outputs


Aug 02, 2021
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira

* Code: https://dpmd.ai/perceiver-code 

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Object-based attention for spatio-temporal reasoning: Outperforming neuro-symbolic models with flexible distributed architectures


Dec 15, 2020
David Ding, Felix Hill, Adam Santoro, Matt Botvinick

* 22 pages, 5 figures 

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Adapting Behaviour for Learning Progress


Dec 14, 2019
Tom Schaul, Diana Borsa, David Ding, David Szepesvari, Georg Ostrovski, Will Dabney, Simon Osindero


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OpenSpiel: A Framework for Reinforcement Learning in Games


Oct 10, 2019
Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinicius 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 Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis


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Deep Lattice Networks and Partial Monotonic Functions


Sep 19, 2017
Seungil You, David Ding, Kevin Canini, Jan Pfeifer, Maya Gupta

* 9 pages, NIPS 2017 

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