Lawrence Phillips | DeepAI

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Featured Co-authors

Nathan O. Hodas
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Brian Hutchinson
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Francesco Farina
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Konstantinos Kalogeropoulos
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Courtney D. Corley
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Scott Howland
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Nathan Hilliard
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∙ 04/29/2022

Bayesian Benefit Risk Analysis

The process of approving and assessing new drugs is often quite complica...

0 Konstantinos Vamvourellis, et al. ∙

∙ 07/06/2021

Intrinsic uncertainties and where to find them

We introduce a framework for uncertainty estimation that both describes ...

0 Francesco Farina, et al. ∙

∙ 11/15/2019

Explanatory Masks for Neural Network Interpretability

Neural network interpretability is a vital component for applications ac...

0 Lawrence Phillips, et al. ∙

∙ 09/14/2019

Metric-Based Few-Shot Learning for Video Action Recognition

In the few-shot scenario, a learner must effectively generalize to unsee...

0 Chris Careaga, et al. ∙

∙ 08/06/2019

Sparse hierarchical representation learning on molecular graphs

Architectures for sparse hierarchical representation learning have recen...

0 Matthias Bal, et al. ∙

∙ 02/12/2018

Few-Shot Learning with Metric-Agnostic Conditional Embeddings

Learning high quality class representations from few examples is a key p...

0 Nathan Hilliard, et al. ∙

∙ 06/06/2017

Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks

Increasingly, cognitive scientists have demonstrated interest in applyin...

0 Lawrence Phillips, et al. ∙

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