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20212024
most citedDynamic-OFA: Runtime DNN Architecture Switching for Performance Scaling on Heterogeneous Embedded Platforms

4 citations · 9 across the 12 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.NE2021★ 1 cited

Learning Division with Neural Arithmetic Logic Modules

Bhumika Mistry, Katayoun Farrahi, Jonathon Hare

To achieve systematic generalisation, it first makes sense to master simple tasks such as arithmetic. Of the four fundamental arithmetic operations (+,-,,), division is…

cs.LG2021

Shared Visual Representations of Drawing for Communication: How do different biases affect human interpretability and intent?

Daniela Mihai, Jonathon Hare

We present an investigation into how representational losses can affect the drawings produced by artificial agents playing a communication game. Building upon recent advances, we s…

cs.LG2021

GhostShiftAddNet: More Features from Energy-Efficient Operations

Jia Bi, Jonathon Hare, Geoff V. Merrett

Deep convolutional neural networks (CNNs) are computationally and memory intensive. In CNNs, intensive multiplication can have resource implications that may challenge the ability…

cs.CL2021

Dynamic Transformer for Efficient Machine Translation on Embedded Devices

Hishan Parry, Lei Xun, Amin Sabet +3

The Transformer architecture is widely used for machine translation tasks. However, its resource-intensive nature makes it challenging to implement on constrained embedded devices,…

cs.CV2021

Temporal Early Exits for Efficient Video Object Detection

Amin Sabet, Jonathon Hare, Bashir Al-Hashimi +1

Transferring image-based object detectors to the domain of video remains challenging under resource constraints. Previous efforts utilised optical flow to allow unchanged features…

cs.CV2021★ 4 cited

Dynamic-OFA: Runtime DNN Architecture Switching for Performance Scaling on Heterogeneous Embedded Platforms

Wei Lou, Lei Xun, Amin Sabet +3

Mobile and embedded platforms are increasingly required to efficiently execute computationally demanding DNNs across heterogeneous processing elements. At runtime, the available ha…

cs.NE2021★ 1 cited

A Primer for Neural Arithmetic Logic Modules

Bhumika Mistry, Katayoun Farrahi, Jonathon Hare

Neural Arithmetic Logic Modules have become a growing area of interest, though remain a niche field. These modules are neural networks which aim to achieve systematic generalisatio…