Elliot J. Crowley | DeepAI

DeepAI AI Chat

Featured Co-authors

Amos Storkey
54 publications
Lichao Huang
20 publications
José Cano
19 publications
Michael O'Boyle
14 publications
Massimiliano Patacchiola
13 publications
Agnieszka Słowik
13 publications
Jack Turner
10 publications
Perry Gibson
10 publications
Valentin Radu
9 publications
Amos J. Storkey
9 publications
Antreas Antoniou
9 publications

∙ 08/31/2023

Generate Your Own Scotland: Satellite Image Generation Conditioned on Maps

Despite recent advancements in image generation, diffusion models still ...

0 Miguel Espinosa, et al. ∙

∙ 11/21/2022

Plug and Play Active Learning for Object Detection

Annotating data for supervised learning is expensive and tedious, and we...

0 Chenhongyi Yang, et al. ∙

∙ 03/10/2022

Prediction-Guided Distillation for Dense Object Detection

Real-world object detection models should be cheap and accurate. Knowled...

0 Chenhongyi Yang, et al. ∙

∙ 11/26/2021

Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning

The goal of contrastive learning based pre-training is to leverage large...

0 Chenhongyi Yang, et al. ∙

∙ 02/12/2021

Neural Architecture Search as Program Transformation Exploration

Improving the performance of deep neural networks (DNNs) is important to...

0 Jack Turner, et al. ∙

∙ 06/17/2020

Optimizing Grouped Convolutions on Edge Devices

When deploying a deep neural network on constrained hardware, it is poss...

11 Perry Gibson, et al. ∙

∙ 06/08/2020

Neural Architecture Search without Training

The time and effort involved in hand-designing deep neural networks is i...

7 Joseph Mellor, et al. ∙

∙ 02/20/2020

Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs

Convolutional Neural Networks (CNN) are becoming a common presence in ma...

7 Valentin Radu, et al. ∙

∙ 10/11/2019

Deep Kernel Transfer in Gaussian Processes for Few-shot Learning

Humans tackle new problems by making inferences that go far beyond the i...

31 Massimiliano Patacchiola, et al. ∙

∙ 06/10/2019

BlockSwap: Fisher-guided Block Substitution for Network Compression

The desire to run neural networks on low-capacity edge devices has led t...

2 Jack Turner, et al. ∙

∙ 06/03/2019

Separable Layers Enable Structured Efficient Linear Substitutions

In response to the development of recent efficient dense layers, this pa...

2 Gavin Gray, et al. ∙

∙ 11/01/2018

Dilated DenseNets for Relational Reasoning

Despite their impressive performance in many tasks, deep neural networks...

11 Antreas Antoniou, et al. ∙

∙ 10/24/2018

HAKD: Hardware Aware Knowledge Distillation

Despite recent developments, deploying deep neural networks on resource ...

10 Jack Turner, et al. ∙

∙ 10/24/2018

Distilling with Performance Enhanced Students

The task of accelerating large neural networks on general purpose hardwa...

0 Jack Turner, et al. ∙

∙ 10/10/2018

Pruning neural networks: is it time to nip it in the bud?

Pruning is a popular technique for compressing a neural network: a large...

6 Elliot J. Crowley, et al. ∙

∙ 10/02/2018

CINIC-10 is not ImageNet or CIFAR-10

In this brief technical report we introduce the CINIC-10 dataset as a pl...

0 Luke N. Darlow, et al. ∙

∙ 09/19/2018

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are extremely computationally deman...

4 Jack Turner, et al. ∙

∙ 11/07/2017

Moonshine: Distilling with Cheap Convolutions

Model distillation compresses a trained machine learning model, such as ...

0 Elliot J. Crowley, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world