5 citations · 8 across the 5 of their papers we have counts for
5 papers
Reproducing BowNet: Learning Representations by Predicting Bags of Visual Words
Harry Nguyen, Stone Yun, Hisham Mohammad
This work aims to reproduce results from the CVPR 2020 paper by Gidaris et al. Self-supervised learning (SSL) is used to learn feature representations of an image using an unlabele…
Dream to Explore: Adaptive Simulations for Autonomous Systems
Zahra Sheikhbahaee, Dongshu Luo, Blake VanBerlo +3
One's ability to learn a generative model of the world without supervision depends on the extent to which one can construct abstract knowledge representations that generalize acros…
Do All MobileNets Quantize Poorly? Gaining Insights into the Effect of Quantization on Depthwise Separable Convolutional Networks Through the Eyes of Multi-scale Distributional Dynamics
Stone Yun, Alexander Wong
As the "Mobile AI" revolution continues to grow, so does the need to understand the behaviour of edge-deployed deep neural networks. In particular, MobileNets are the go-to family…
FactorizeNet: Progressive Depth Factorization for Efficient Network Architecture Exploration Under Quantization Constraints
Stone Yun, Alexander Wong
Depth factorization and quantization have emerged as two of the principal strategies for designing efficient deep convolutional neural network (CNN) architectures tailored for low-…
Where Should We Begin? A Low-Level Exploration of Weight Initialization Impact on Quantized Behaviour of Deep Neural Networks
Stone Yun, Alexander Wong
With the proliferation of deep convolutional neural network (CNN) algorithms for mobile processing, limited precision quantization has become an essential tool for CNN efficiency.…