Comb filter decomposition for robust ASR. - Lech Szymanski; Martin Bouchard 001 (INTERSPEECH, 2005)

Push-pull separability objective for supervised layer-wise training of neural networks. - Lech Szymanski; Brendan McCane (IJCNN, 2012)

Deep, super-narrow neural network is a universal classifier. - Lech Szymanski; Brendan McCane (IJCNN, 2012)

Learning in deep architectures with folding transformations. - Lech Szymanski; Brendan McCane (IJCNN, 2013)

Singularity resolution for dimension reduction. - Shawn Martin; Lech Szymanski (IVCNZ, 2013)

Hierarchical Structure from Motion from Endoscopic Video. - Steven Mills; Lech Szymanski; Reuben Johnson (IVCNZ, 2014)

Deep Networks are Effective Encoders of Periodicity. - Lech Szymanski; Brendan McCane (IEEE Trans. Neural Networks Learn. Syst., 2014)

Deep networks are efficient for circular manifolds. - Brendan McCane; Lech Szymanski (ICPR, 2016)

Auto-JacoBin: Auto-encoder Jacobian Binary Hashing. - Xiping Fu; Brendan McCane; Steven Mills; Michael H. Albert; Lech Szymanski (CoRR, 2016)

SIFT10M. - Xiping Fu; Brendan McCane; Steven Mills; Michael H. Albert; Lech Szymanski (UCI Machine Learning Repository, 2016)

Increasing the accuracy of convolutional neural networks with progressive reinitialisation. - Craig Atkinson; Brendan McCane; Lech Szymanski (IVCNZ, 2017)

CNN for historic handwritten document search. - Lech Szymanski; Steven Mills (IVCNZ, 2017)

Deep Radial Kernel Networks: Approximating Radially Symmetric Functions with Deep Networks. - Brendan McCane; Lech Szymanski (CoRR, 2017)

Effects of the optimisation of the margin distribution on generalisation in deep architectures. - Lech Szymanski; Brendan McCane; Wei Gao 008; Zhi-Hua Zhou (CoRR, 2017)

Twin Bounded Large Margin Distribution Machine. - Haitao Xu; Brendan McCane; Lech Szymanski (Australasian Conference on Artificial Intelligence, 2018)

Stacked Hourglass CNN for Handwritten Character Location. - Hannah Clark-Younger; Steven Mills; Lech Szymanski (IVCNZ, 2018)

Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural Networks. - Craig Atkinson; Brendan McCane; Lech Szymanski; Anthony V. Robins (CoRR, 2018)

Some Approximation Bounds for Deep Networks. - Brendan McCane; Lech Szymanski (CoRR, 2018)

The effect of the choice of neural network depth and breadth on the size of its hypothesis space. - Lech Szymanski; Brendan McCane; Michael H. Albert (CoRR, 2018)

Efficiency of deep networks for radially symmetric functions. - Brendan McCane; Lech Szymanski (Neurocomputing, 2018)

A Convolutional Self-organizing Map for Visual Category Learning. - Chris Gorman; Lech Szymanski; Anthony V. Robins; Alistair Knott (CogSci, 2019)

Switched linear projections and inactive state sensitivity for deep neural network interpretability. - Lech Szymanski; Brendan McCane; Craig Atkinson (CoRR, 2019)

GRIm-RePR: Prioritising Generating Important Features for Pseudo-Rehearsal. - Craig Atkinson; Brendan McCane; Lech Szymanski; Anthony V. Robins (CoRR, 2019)

Predicting Cherry Quality Using Siamese Networks. - Yerren van Sint Annaland; Lech Szymanski; Steven Mills (IVCNZ, 2020)

Deep Sheep: kinship assignment in livestock from facial images. - Lech Szymanski; Michael Lee (IVCNZ, 2020)

MIME: Mutual Information Minimisation Exploration. - Haitao Xu; Brendan McCane; Lech Szymanski; Craig Atkinson (CoRR, 2020)

Coarse facial feature detection in sheep. - Lech Szymanski; Michael Lee (IVCNZ, 2021)

Conceptual capacity and effective complexity of neural networks. - Lech Szymanski; Brendan McCane; Craig Atkinson (CoRR, 2021)

Pseudo-rehearsal: Achieving deep reinforcement learning without catastrophic forgetting. - Craig Atkinson; Brendan McCane; Lech Szymanski; Anthony V. Robins (Neurocomputing, 2021)

Conceptual complexity of neural networks. - Lech Szymanski; Brendan McCane; Craig Atkinson (Neurocomputing, 2022)

VASE: Variational Assorted Surprise Exploration for Reinforcement Learning. - Haitao Xu; Lech Szymanski; Brendan McCane (IEEE Trans. Neural Networks Learn. Syst., 2023)

Investigating Feature Clustering for Generalised 3D Point Cloud Part Segmentation. - Nirmal Das; Steven Mills; Lech Szymanski; Xinyu Jiang; Tapabrata Chakraborti (IVCNZ, 2024)

Image Segmentation with a Deep Declarative Network. - Lech Szymanski; Steven Mills; Garth Wales; Hayden McAlister (IVCNZ, 2024)

Improved Robustness and Hyperparameter Selection in Modern Hopfield Networks. - Hayden McAlister; Anthony V. Robins; Lech Szymanski (CoRR, 2024)

Sequential Learning in the Dense Associative Memory. - Hayden McAlister; Anthony V. Robins; Lech Szymanski (CoRR, 2024)

Prototype Analysis in Hopfield Networks With Hebbian Learning. - Hayden McAlister; Anthony V. Robins; Lech Szymanski (Neural Comput., 2024)

Classifying States of the Hopfield Network with Improved Accuracy, Generalization, and Interpretability. - Hayden McAlister; Anthony V. Robins; Lech Szymanski (CoRR, 2025)