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Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Multimodal learning for generative models often refers to the learning o...
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Rethinking Semi-Supervised Learning in VAEs
We present an alternative approach to semi-supervision in variational au...
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Simulation-Based Inference for Global Health Decisions
The COVID-19 pandemic has highlighted the importance of in-silico epidem...
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A Revised Generative Evaluation of Visual Dialogue
Evaluating Visual Dialogue, the task of answering a sequence of question...
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Lessons from reinforcement learning for biological representations of space
Neuroscientists postulate 3D representations in the brain in a variety o...
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Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models
Learning generative models that span multiple data modalities, such as v...
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Multitask Soft Option Learning
We present Multitask Soft Option Learning (MSOL), a hierarchical multita...
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Visual Dialogue without Vision or Dialogue
We characterise some of the quirks and shortcomings in the exploration o...
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Revisiting Reweighted Wake-Sleep
Discrete latent-variable models, while applicable in a variety of settin...
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DGPose: Disentangled Semi-supervised Deep Generative Models for Human Body Analysis
Deep generative modelling for robust human body analysis is an emerging ...
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FlipDial: A Generative Model for Two-Way Visual Dialogue
We present FlipDial, a generative model for visual dialogue that simulta...
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Faithful Model Inversion Substantially Improves Auto-encoding Variational Inference
In learning deep generative models, the encoder for variational inferenc...
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Learning Disentangled Representations with Semi-Supervised Deep Generative Models
Variational autoencoders (VAEs) learn representations of data by jointly...
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Playing Doom with SLAM-Augmented Deep Reinforcement Learning
A number of recent approaches to policy learning in 2D game domains have...
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Inducing Interpretable Representations with Variational Autoencoders
We develop a framework for incorporating structured graphical models in ...
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Coarse-to-Fine Sequential Monte Carlo for Probabilistic Programs
Many practical techniques for probabilistic inference require a sequence...
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Saying What You're Looking For: Linguistics Meets Video Search
We present an approach to searching large video corpora for video clips ...
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Seeing What You're Told: Sentence-Guided Activity Recognition In Video
We present a system that demonstrates how the compositional structure of...
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