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06/17/2022
Evolution through Large Models
This paper pursues the insight that large language models (LLMs) trained...
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01/10/2021
The Gaussian Neural Process
Neural Processes (NPs; Garnelo et al., 2018a,b) are a rich class of mode...
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07/02/2020
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
Stationary stochastic processes (SPs) are a key component of many probab...
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06/18/2020
Predictive Complexity Priors
Specifying a Bayesian prior is notoriously difficult for complex models ...
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03/06/2020
TaskNorm: Rethinking Batch Normalization for Meta-Learning
Modern meta-learning approaches for image classification rely on increas...
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10/29/2019
Convolutional Conditional Neural Processes
We introduce the Convolutional Conditional Neural Process (ConvCNP), a n...
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08/06/2019
Bayesian Batch Active Learning as Sparse Subset Approximation
Leveraging the wealth of unlabeled data produced in recent years provide...
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06/18/2019
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
The goal of this paper is to design image classification systems that, a...
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02/13/2019
Probabilistic Neural Architecture Search
In neural architecture search (NAS), the space of neural network archite...
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05/24/2018
Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning
This paper develops a general framework for data efficient and versatile...
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08/01/2017
An Investigation into the Pedagogical Features of Documents
Characterizing the content of a technical document in terms of its learn...
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06/29/2017
