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08/31/2023
Generate Your Own Scotland: Satellite Image Generation Conditioned on Maps
Despite recent advancements in image generation, diffusion models still ...
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11/21/2022
Plug and Play Active Learning for Object Detection
Annotating data for supervised learning is expensive and tedious, and we...
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03/10/2022
Prediction-Guided Distillation for Dense Object Detection
Real-world object detection models should be cheap and accurate. Knowled...
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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...
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02/12/2021
Neural Architecture Search as Program Transformation Exploration
Improving the performance of deep neural networks (DNNs) is important to...
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06/17/2020
Optimizing Grouped Convolutions on Edge Devices
When deploying a deep neural network on constrained hardware, it is poss...
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06/08/2020
Neural Architecture Search without Training
The time and effort involved in hand-designing deep neural networks is i...
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02/20/2020
Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs
Convolutional Neural Networks (CNN) are becoming a common presence in ma...
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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...
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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...
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06/03/2019
Separable Layers Enable Structured Efficient Linear Substitutions
In response to the development of recent efficient dense layers, this pa...
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11/01/2018
Dilated DenseNets for Relational Reasoning
Despite their impressive performance in many tasks, deep neural networks...
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10/24/2018
HAKD: Hardware Aware Knowledge Distillation
Despite recent developments, deploying deep neural networks on resource ...
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10/24/2018
Distilling with Performance Enhanced Students
The task of accelerating large neural networks on general purpose hardwa...
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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...
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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...
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09/19/2018
Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are extremely computationally deman...
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11/07/2017
