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06/13/2023
DreamDecompiler: Improved Bayesian Program Learning by Decompiling Amortised Knowledge
Solving program induction problems requires searching through an enormou...
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05/29/2023
Autoencoding Conditional Neural Processes for Representation Learning
Conditional neural processes (CNPs) are a flexible and efficient family ...
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05/09/2023
StrAE: Autoencoding for Pre-Trained Embeddings using Explicit Structure
This work explores the utility of explicit structure for representation ...
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06/03/2022
Drawing out of Distribution with Neuro-Symbolic Generative Models
Learning general-purpose representations from perceptual inputs is a hal...
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01/31/2022
Adversarial Masking for Self-Supervised Learning
We propose ADIOS, a masked image model (MIM) framework for self-supervis...
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06/25/2021
InteL-VAEs: Adding Inductive Biases to Variational Auto-Encoders via Intermediary Latents
We introduce a simple and effective method for learning VAEs with contro...
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06/23/2021
Learning Multimodal VAEs through Mutual Supervision
Multimodal VAEs seek to model the joint distribution over heterogeneous ...
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04/20/2021
Gradient Matching for Domain Generalization
Machine learning systems typically assume that the distributions of trai...
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07/02/2020
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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06/17/2020
Rethinking Semi-Supervised Learning in VAEs
We present an alternative approach to semi-supervision in variational au...
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05/14/2020
Simulation-Based Inference for Global Health Decisions
The COVID-19 pandemic has highlighted the importance of in-silico epidem...
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04/20/2020
A Revised Generative Evaluation of Visual Dialogue
Evaluating Visual Dialogue, the task of answering a sequence of question...
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12/13/2019
Lessons from reinforcement learning for biological representations of space
Neuroscientists postulate 3D representations in the brain in a variety o...
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11/08/2019
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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04/01/2019
Multitask Soft Option Learning
We present Multitask Soft Option Learning (MSOL), a hierarchical multita...
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12/16/2018
Visual Dialogue without Vision or Dialogue
We characterise some of the quirks and shortcomings in the exploration o...
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05/26/2018
Revisiting Reweighted Wake-Sleep
Discrete latent-variable models, while applicable in a variety of settin...
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04/17/2018
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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02/11/2018
FlipDial: A Generative Model for Two-Way Visual Dialogue
We present FlipDial, a generative model for visual dialogue that simulta...
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12/01/2017
Faithful Model Inversion Substantially Improves Auto-encoding Variational Inference
In learning deep generative models, the encoder for variational inferenc...
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06/01/2017
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
Variational autoencoders (VAEs) learn representations of data by jointly...
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12/01/2016
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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11/22/2016
Inducing Interpretable Representations with Variational Autoencoders
We develop a framework for incorporating structured graphical models in ...
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09/09/2015
Coarse-to-Fine Sequential Monte Carlo for Probabilistic Programs
Many practical techniques for probabilistic inference require a sequence...
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09/20/2013
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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08/19/2013