Lech Szymanski

40 papers A 1B 5Misc 10Journal 23Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Classifying States of the Hopfield Network with Improved Accuracy, Generalization, and Interpretability. CoRR Hayden McAlister, Anthony V. Robins, Lech Szymanski
2025	J	`jnl`	Sequential Learning in the Dense Associative Memory. Neural Comput. Hayden McAlister, Anthony V. Robins, Lech Szymanski
2024	Misc	`conf`	Image Segmentation with a Deep Declarative Network. IVCNZ Lech Szymanski, Steven Mills, Garth Wales, Hayden McAlister
2024	J	`jnl`	Improved Robustness and Hyperparameter Selection in Modern Hopfield Networks. CoRR Hayden McAlister, Anthony V. Robins, Lech Szymanski
2024	Misc	`conf`	Investigating Feature Clustering for Generalised 3D Point Cloud Part Segmentation. IVCNZ Nirmal Das, Steven Mills, Lech Szymanski, Xinyu Jiang, Tapabrata Chakraborti
2024	J	`jnl`	Prototype Analysis in Hopfield Networks With Hebbian Learning. Neural Comput. Hayden McAlister, Anthony V. Robins, Lech Szymanski
2024	J	`jnl`	Prototype Analysis in Hopfield Networks with Hebbian Learning. CoRR Hayden McAlister, Anthony V. Robins, Lech Szymanski
2024	J	`jnl`	Sequential Learning in the Dense Associative Memory. CoRR Hayden McAlister, Anthony V. Robins, Lech Szymanski
2023	J	`jnl`	VASE: Variational Assorted Surprise Exploration for Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. Haitao Xu, Lech Szymanski, Brendan McCane
2022	J	`jnl`	Conceptual complexity of neural networks. Neurocomputing Lech Szymanski, Brendan McCane, Craig Atkinson
2021	Misc	`conf`	Coarse facial feature detection in sheep. IVCNZ Lech Szymanski, Michael Lee
2021	J	`jnl`	Conceptual capacity and effective complexity of neural networks. CoRR Lech Szymanski, Brendan McCane, Craig Atkinson
2021	J	`jnl`	Pseudo-rehearsal: Achieving deep reinforcement learning without catastrophic forgetting. Neurocomputing Craig Atkinson, Brendan McCane, Lech Szymanski, Anthony V. Robins
2020	Misc	`conf`	Deep Sheep: kinship assignment in livestock from facial images. IVCNZ Lech Szymanski, Michael Lee
2020	J	`jnl`	MIME: Mutual Information Minimisation Exploration. CoRR Haitao Xu, Brendan McCane, Lech Szymanski, Craig Atkinson
2020	Misc	`conf`	Predicting Cherry Quality Using Siamese Networks. IVCNZ Yerren van Sint Annaland, Lech Szymanski, Steven Mills
2019	B	`conf`	A Convolutional Self-organizing Map for Visual Category Learning. CogSci Chris Gorman, Lech Szymanski, Anthony V. Robins, Alistair Knott
2019	J	`jnl`	GRIm-RePR: Prioritising Generating Important Features for Pseudo-Rehearsal. CoRR Craig Atkinson, Brendan McCane, Lech Szymanski, Anthony V. Robins
2019	J	`jnl`	Switched linear projections and inactive state sensitivity for deep neural network interpretability. CoRR Lech Szymanski, Brendan McCane, Craig Atkinson
2019	J	`jnl`	VASE: Variational Assorted Surprise Exploration for Reinforcement Learning. CoRR Haitao Xu, Brendan McCane, Lech Szymanski
2018	J	`jnl`	Efficiency of deep networks for radially symmetric functions. Neurocomputing Brendan McCane, Lech Szymanski
2018	J	`jnl`	Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural Networks. CoRR Craig Atkinson, Brendan McCane, Lech Szymanski, Anthony V. Robins
2018	J	`jnl`	Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting. CoRR Craig Atkinson, Brendan McCane, Lech Szymanski, Anthony V. Robins
2018	J	`jnl`	Some Approximation Bounds for Deep Networks. CoRR Brendan McCane, Lech Szymanski
2018	Misc	`conf`	Stacked Hourglass CNN for Handwritten Character Location. IVCNZ Hannah Clark-Younger, Steven Mills, Lech Szymanski
2018	J	`jnl`	The effect of the choice of neural network depth and breadth on the size of its hypothesis space. CoRR Lech Szymanski, Brendan McCane, Michael H. Albert
2018	—	`conf`	Twin Bounded Large Margin Distribution Machine. Australasian Conference on Artificial Intelligence Haitao Xu, Brendan McCane, Lech Szymanski
2017	Misc	`conf`	CNN for historic handwritten document search. IVCNZ Lech Szymanski, Steven Mills
2017	J	`jnl`	Deep Radial Kernel Networks: Approximating Radially Symmetric Functions with Deep Networks. CoRR Brendan McCane, Lech Szymanski
2017	J	`jnl`	Effects of the optimisation of the margin distribution on generalisation in deep architectures. CoRR Lech Szymanski, Brendan McCane, Wei Gao, Zhi-Hua Zhou
2017	Misc	`conf`	Increasing the accuracy of convolutional neural networks with progressive reinitialisation. IVCNZ Craig Atkinson, Brendan McCane, Lech Szymanski
2016	J	`jnl`	Auto-JacoBin: Auto-encoder Jacobian Binary Hashing. CoRR Xiping Fu, Brendan McCane, Steven Mills, Michael H. Albert, Lech Szymanski
2016	B	`conf`	Deep networks are efficient for circular manifolds. ICPR Brendan McCane, Lech Szymanski
2014	J	`jnl`	Deep Networks are Effective Encoders of Periodicity. IEEE Trans. Neural Networks Learn. Syst. Lech Szymanski, Brendan McCane
2014	Misc	`conf`	Hierarchical Structure from Motion from Endoscopic Video. IVCNZ Steven Mills, Lech Szymanski, Reuben Johnson
2013	B	`conf`	Learning in deep architectures with folding transformations. IJCNN Lech Szymanski, Brendan McCane
2013	Misc	`conf`	Singularity resolution for dimension reduction. IVCNZ Shawn Martin, Lech Szymanski
2012	B	`conf`	Deep, super-narrow neural network is a universal classifier. IJCNN Lech Szymanski, Brendan McCane
2012	B	`conf`	Push-pull separability objective for supervised layer-wise training of neural networks. IJCNN Lech Szymanski, Brendan McCane
2005	A	`conf`	Comb filter decomposition for robust ASR. INTERSPEECH Lech Szymanski, Martin Bouchard