
Pick Your Battles: Interaction Graphs as PopulationLevel Objectives for Strategic Diversity
Strategic diversity is often essential in games: in multiplayer games, ...
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Inferring a Continuous Distribution of Atom Coordinates from CryoEM Images using VAEs
Cryoelectron microscopy (cryoEM) has revolutionized experimental prote...
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Timeseries Imputation of Temporallyoccluded Multiagent Trajectories
In multiagent environments, several decisionmaking individuals interact...
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Game Plan: What AI can do for Football, and What Football can do for AI
The rapid progress in artificial intelligence (AI) and machine learning ...
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AlignNet: Unsupervised Entity Alignment
Recently developed deep learning models are able to learn to segment sce...
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Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about MixedNash and Love Neural Nets
Adversarial training, a special case of multiobjective optimization, is...
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A Neural Architecture for Designing Truthful and Efficient Auctions
Auctions are protocols to allocate goods to buyers who have preferences ...
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An Explicitly Relational Neural Network Architecture
With a view to bridging the gap between deep learning and symbolic AI, w...
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MetaLearning surrogate models for sequential decision making
Metalearning methods leverage past experience to learn datadriven indu...
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Adaptive Posterior Learning: fewshot learning with a surprisebased memory module
The ability to generalize quickly from few observations is crucial for i...
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Openended Learning in Symmetric Zerosum Games
Zerosum games such as chess and poker are, abstractly, functions that e...
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Attentive Neural Processes
Neural Processes (NPs) (Garnelo et al 2018a;b) approach regression by le...
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Verification of deep probabilistic models
Probabilistic models are a critical part of the modern deep learning too...
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Consistent Generative Query Networks
Stochastic video prediction is usually framed as an extrapolation proble...
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Neural Processes
A neural network (NN) is a parameterised function that can be tuned via ...
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Conditional Neural Processes
Deep neural networks excel at function approximation, yet they are typic...
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Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders
We study a variant of the variational autoencoder model (VAE) with a Gau...
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Towards Deep Symbolic Reinforcement Learning
Deep reinforcement learning (DRL) brings the power of deep neural networ...
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Marta Garnelo
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