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ORCIDAndrew Hryniowski
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2020 – today
- 2024
[b1]Andrew Hryniowski:
A Representational Response Analysis Framework For Convolutional Neural Networks. University of Waterloo, Ontario, Canada, 2024- 2023
- [c2]Andrew Hryniowski, Alexander Wong:
Systematic Architectural Design of Scale Transformed Attention Condenser DNNs via Multi-Scale Class Representational Response Similarity Analysis. CVPR Workshops 2023: 2284-2292 - [i13]Andrew Hryniowski, Alexander Wong:
Systematic Architectural Design of Scale Transformed Attention Condenser DNNs via Multi-Scale Class Representational Response Similarity Analysis. CoRR abs/2306.10128 (2023) - [i12]Audrey G. Chung, Francis Li, Jeremy Ward, Andrew Hryniowski, Alexander Wong:
DVQI: A Multi-task, Hardware-integrated Artificial Intelligence System for Automated Visual Inspection in Electronics Manufacturing. CoRR abs/2312.09232 (2023) - 2022
- [i11]Hossein Aboutalebi, Maya Pavlova, Mohammad Javad Shafiee, Adrian Florea, Andrew Hryniowski, Alexander Wong:
COVID-Net Biochem: An Explainability-driven Framework to Building Machine Learning Models for Predicting Survival and Kidney Injury of COVID-19 Patients from Clinical and Biochemistry Data. CoRR abs/2204.11210 (2022) - 2021
- [i10]Xiaoyu Wen, Mahmoud Famouri, Andrew Hryniowski, Alexander Wong:
AttendSeg: A Tiny Attention Condenser Neural Network for Semantic Segmentation on the Edge. CoRR abs/2104.14623 (2021) - [i9]Audrey G. Chung, Mahmoud Famouri, Andrew Hryniowski, Alexander Wong:
COVID-Net Clinical ICU: Enhanced Prediction of ICU Admission for COVID-19 Patients via Explainability and Trust Quantification. CoRR abs/2109.06711 (2021) - 2020
- [i8]Alexander Wong, Xiao Yu Wang, Andrew Hryniowski:
How Much Can We Really Trust You? Towards Simple, Interpretable Trust Quantification Metrics for Deep Neural Networks. CoRR abs/2009.05835 (2020) - [i7]Andrew Hryniowski, Xiao Yu Wang, Alexander Wong:
Where Does Trust Break Down? A Quantitative Trust Analysis of Deep Neural Networks via Trust Matrix and Conditional Trust Densities. CoRR abs/2009.14701 (2020) - [i6]Alexander Wong, Andrew Hryniowski, Xiao Yu Wang:
Insights into Fairness through Trust: Multi-scale Trust Quantification for Financial Deep Learning. CoRR abs/2011.01961 (2020) - [i5]Andrew Hryniowski, Alexander Wong:
Inter-layer Information Similarity Assessment of Deep Neural Networks Via Topological Similarity and Persistence Analysis of Data Neighbour Dynamics. CoRR abs/2012.03793 (2020)
2010 – 2019
- 2019
- [i4]Andrew Hryniowski, Alexander Wong:
Seeing Convolution Through the Eyes of Finite Transformation Semigroup Theory: An Abstract Algebraic Interpretation of Convolutional Neural Networks. CoRR abs/1905.10901 (2019) - [i3]Mohammad Javad Shafiee, Andrew Hryniowski, Francis Li, Zhong Qiu Lin, Alexander Wong:
State of Compact Architecture Search For Deep Neural Networks. CoRR abs/1910.06466 (2019) - [i2]Andrew Hryniowski, Alexander Wong:
DeepLABNet: End-to-end Learning of Deep Radial Basis Networks with Fully Learnable Basis Functions. CoRR abs/1911.09257 (2019) - 2018
- [c1]Andrew Hryniowski, Ibrahim Ben Daya, Ahmed Gawish, Mark Lamm, Alexander Wong, Paul W. Fieguth:
Multi-projector Resolution Enhancement Through Biased Interpolation. CRV 2018: 190-197 - [i1]Andrew Hryniowski, Alexander Wong:
PolyNeuron: Automatic Neuron Discovery via Learned Polyharmonic Spline Activations. CoRR abs/1811.04303 (2018)
Coauthor Index
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