Joost van Amersfoort | DeepAI

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∙ 02/16/2022

Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients

Pruning neural networks at initialization would enable us to find sparse...

0 Milad Alizadeh, et al. ∙

∙ 12/01/2021

Decomposing Representations for Deterministic Uncertainty Estimation

Uncertainty estimation is a key component in any deployed machine learni...

0 Haiwen Huang, et al. ∙

∙ 11/03/2021

Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data

Estimating personalized treatment effects from high-dimensional observat...

13 Andrew Jesson, et al. ∙

∙ 10/29/2021

Deep Deterministic Uncertainty for Semantic Segmentation

We extend Deep Deterministic Uncertainty (DDU), a method for uncertainty...

0 Jishnu Mukhoti, et al. ∙

∙ 06/04/2021

Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective

ResNets constrained to be bi-Lipschitz, that is, approximately distance ...

0 Lewis Smith, et al. ∙

∙ 02/23/2021

Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty

We show that a single softmax neural net with minimal changes can beat t...

6 Jishnu Mukhoti, et al. ∙

∙ 02/22/2021

Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression

We propose a new model that estimates uncertainty in a single forward pa...

0 Joost van Amersfoort, et al. ∙

∙ 07/01/2020

Single Shot Structured Pruning Before Training

We introduce a method to speed up training by 2x and inference by 3x in ...

13 Joost van Amersfoort, et al. ∙

∙ 03/04/2020

Simple and Scalable Epistemic Uncertainty Estimation Using a Single Deep Deterministic Neural Network

We propose a method for training a deterministic deep model that can fin...

22 Joost van Amersfoort, et al. ∙

∙ 06/19/2019

BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning

We develop BatchBALD, a tractable approximation to the mutual informatio...

1 Andreas Kirsch, et al. ∙

∙ 02/11/2019

Deep Hashing using Entropy Regularised Product Quantisation Network

In large scale systems, approximate nearest neighbour search is a crucia...

12 Jo Schlemper, et al. ∙

∙ 11/16/2017

Frame Interpolation with Multi-Scale Deep Loss Functions and Generative Adversarial Networks

Frame interpolation attempts to synthesise intermediate frames given one...

0 Joost van Amersfoort, et al. ∙

∙ 01/29/2017

Transformation-Based Models of Video Sequences

In this work we propose a simple unsupervised approach for next frame pr...

0 Joost van Amersfoort, et al. ∙

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