Andrew Hryniowski

16 papers Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	—	`—`	A Representational Response Analysis Framework For Convolutional Neural Networks. Andrew Hryniowski
2023	J	`jnl`	DVQI: A Multi-task, Hardware-integrated Artificial Intelligence System for Automated Visual Inspection in Electronics Manufacturing. CoRR Audrey G. Chung, Francis Li, Jeremy Ward, Andrew Hryniowski, Alexander Wong
2023	—	`conf`	Systematic Architectural Design of Scale Transformed Attention Condenser DNNs via Multi-Scale Class Representational Response Similarity Analysis. CVPR Workshops Andrew Hryniowski, Alexander Wong
2023	J	`jnl`	Systematic Architectural Design of Scale Transformed Attention Condenser DNNs via Multi-Scale Class Representational Response Similarity Analysis. CoRR Andrew Hryniowski, Alexander Wong
2022	J	`jnl`	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 Hossein Aboutalebi, Maya Pavlova, Mohammad Javad Shafiee, Adrian Florea, Andrew Hryniowski, Alexander Wong
2021	J	`jnl`	AttendSeg: A Tiny Attention Condenser Neural Network for Semantic Segmentation on the Edge. CoRR Xiaoyu Wen, Mahmoud Famouri, Andrew Hryniowski, Alexander Wong
2021	J	`jnl`	COVID-Net Clinical ICU: Enhanced Prediction of ICU Admission for COVID-19 Patients via Explainability and Trust Quantification. CoRR Audrey G. Chung, Mahmoud Famouri, Andrew Hryniowski, Alexander Wong
2020	J	`jnl`	How Much Can We Really Trust You? Towards Simple, Interpretable Trust Quantification Metrics for Deep Neural Networks. CoRR Alexander Wong, Xiao Yu Wang, Andrew Hryniowski
2020	J	`jnl`	Insights into Fairness through Trust: Multi-scale Trust Quantification for Financial Deep Learning. CoRR Alexander Wong, Andrew Hryniowski, Xiao Yu Wang
2020	J	`jnl`	Inter-layer Information Similarity Assessment of Deep Neural Networks Via Topological Similarity and Persistence Analysis of Data Neighbour Dynamics. CoRR Andrew Hryniowski, Alexander Wong
2020	J	`jnl`	Where Does Trust Break Down? A Quantitative Trust Analysis of Deep Neural Networks via Trust Matrix and Conditional Trust Densities. CoRR Andrew Hryniowski, Xiao Yu Wang, Alexander Wong
2019	J	`jnl`	DeepLABNet: End-to-end Learning of Deep Radial Basis Networks with Fully Learnable Basis Functions. CoRR Andrew Hryniowski, Alexander Wong
2019	J	`jnl`	Seeing Convolution Through the Eyes of Finite Transformation Semigroup Theory: An Abstract Algebraic Interpretation of Convolutional Neural Networks. CoRR Andrew Hryniowski, Alexander Wong
2019	J	`jnl`	State of Compact Architecture Search For Deep Neural Networks. CoRR Mohammad Javad Shafiee, Andrew Hryniowski, Francis Li, Zhong Qiu Lin, Alexander Wong
2018	—	`conf`	Multi-projector Resolution Enhancement Through Biased Interpolation. CRV Andrew Hryniowski, Ibrahim Ben Daya, Ahmed Gawish, Mark Lamm, Alexander Wong, Paul W. Fieguth
2018	J	`jnl`	PolyNeuron: Automatic Neuron Discovery via Learned Polyharmonic Spline Activations. CoRR Andrew Hryniowski, Alexander Wong