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05/17/2023
Exploring the Space of Key-Value-Query Models with Intention
Attention-based models have been a key element of many recent breakthrou...
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10/08/2021
Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity
Strategic diversity is often essential in games: in multi-player games, ...
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06/26/2021
Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs
Cryo-electron microscopy (cryo-EM) has revolutionized experimental prote...
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06/08/2021
Time-series Imputation of Temporally-occluded Multiagent Trajectories
In multiagent environments, several decision-making individuals interact...
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11/18/2020
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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07/17/2020
AlignNet: Unsupervised Entity Alignment
Recently developed deep learning models are able to learn to segment sce...
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02/14/2020
Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
Adversarial training, a special case of multi-objective optimization, is...
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07/11/2019
A Neural Architecture for Designing Truthful and Efficient Auctions
Auctions are protocols to allocate goods to buyers who have preferences ...
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05/24/2019
An Explicitly Relational Neural Network Architecture
With a view to bridging the gap between deep learning and symbolic AI, w...
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03/28/2019
Meta-Learning surrogate models for sequential decision making
Meta-learning methods leverage past experience to learn data-driven indu...
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02/07/2019
Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
The ability to generalize quickly from few observations is crucial for i...
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01/23/2019
Open-ended Learning in Symmetric Zero-sum Games
Zero-sum games such as chess and poker are, abstractly, functions that e...
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01/17/2019
Attentive Neural Processes
Neural Processes (NPs) (Garnelo et al 2018a;b) approach regression by le...
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12/06/2018
Verification of deep probabilistic models
Probabilistic models are a critical part of the modern deep learning too...
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07/05/2018
Consistent Generative Query Networks
Stochastic video prediction is usually framed as an extrapolation proble...
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07/04/2018
Neural Processes
A neural network (NN) is a parameterised function that can be tuned via ...
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07/04/2018
Conditional Neural Processes
Deep neural networks excel at function approximation, yet they are typic...
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11/08/2016
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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09/18/2016