Marta Garnelo

According to our database1, Marta Garnelo authored at least 23 papers between 2016 and 2023.

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Bibliography

2023
Exploring the Space of Key-Value-Query Models with Intention.
CoRR, 2023

2021
Incorporating prior knowledge into deep neural networks without handcrafted features
PhD thesis, 2021

Game Plan: What AI can do for Football, and What Football can do for AI.
J. Artif. Intell. Res., 2021

Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs.
CoRR, 2021

Time-series Imputation of Temporally-occluded Multiagent Trajectories.
CoRR, 2021

Game-theoretic Vocabulary Selection via the Shapley Value and Banzhaf Index.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

A Neural Network Auction For Group Decision Making Over a Continuous Space.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
AlignNet: Unsupervised Entity Alignment.
CoRR, 2020

Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets.
CoRR, 2020

An Explicitly Relational Neural Network Architecture.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
A Neural Architecture for Designing Truthful and Efficient Auctions.
CoRR, 2019

Meta-Learning surrogate models for sequential decision making.
CoRR, 2019

Open-ended learning in symmetric zero-sum games.
Proceedings of the 36th International Conference on Machine Learning, 2019

Adaptive Posterior Learning: few-shot learning with a surprise-based memory module.
Proceedings of the 7th International Conference on Learning Representations, 2019

Attentive Neural Processes.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Verification of deep probabilistic models.
CoRR, 2018

Consistent Generative Query Networks.
CoRR, 2018

Neural Processes.
CoRR, 2018

Conditional Neural Processes.
Proceedings of the 35th International Conference on Machine Learning, 2018

2016
Towards Deep Symbolic Reinforcement Learning.
CoRR, 2016

Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders.
CoRR, 2016


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