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2020 – today
- 2024
[i15]Hayden McAlister, Anthony Robins, Lech Szymanski:
Prototype Analysis in Hopfield Networks with Hebbian Learning. CoRR abs/2407.03342 (2024)- [i14]Hayden McAlister, Anthony Robins, Lech Szymanski:
Improved Robustness and Hyperparameter Selection in Modern Hopfield Networks. CoRR abs/2407.08742 (2024) - [i13]Hayden McAlister, Anthony Robins, Lech Szymanski:
Sequential Learning in the Dense Associative Memory. CoRR abs/2409.15729 (2024) - 2023
- [j5]Haitao Xu
, Lech Szymanski, Brendan McCane:
VASE: Variational Assorted Surprise Exploration for Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. 34(3): 1243-1252 (2023) - 2022
- [j4]Lech Szymanski, Brendan McCane, Craig Atkinson:
Conceptual complexity of neural networks. Neurocomputing 469: 52-64 (2022) - 2021
- [j3]Craig Atkinson, Brendan McCane, Lech Szymanski, Anthony V. Robins:
Pseudo-rehearsal: Achieving deep reinforcement learning without catastrophic forgetting. Neurocomputing 428: 291-307 (2021) - [c15]Lech Szymanski, Michael Lee:
Coarse facial feature detection in sheep. IVCNZ 2021: 1-6 - [i12]Lech Szymanski, Brendan McCane, Craig Atkinson:
Conceptual capacity and effective complexity of neural networks. CoRR abs/2103.07614 (2021) - 2020
- [c14]Yerren van Sint Annaland, Lech Szymanski, Steven Mills:
Predicting Cherry Quality Using Siamese Networks. IVCNZ 2020: 1-6 - [c13]Lech Szymanski, Michael Lee:
Deep Sheep: kinship assignment in livestock from facial images. IVCNZ 2020: 1-6 - [i11]Haitao Xu, Brendan McCane, Lech Szymanski, Craig Atkinson:
MIME: Mutual Information Minimisation Exploration. CoRR abs/2001.05636 (2020)
2010 – 2019
- 2019
- [c12]Chris Gorman, Lech Szymanski, Anthony V. Robins, Alistair Knott:
A Convolutional Self-organizing Map for Visual Category Learning. CogSci 2019: 3275 - [i10]Lech Szymanski, Brendan McCane, Craig Atkinson:
Switched linear projections and inactive state sensitivity for deep neural network interpretability. CoRR abs/1909.11275 (2019) - [i9]Haitao Xu, Brendan McCane, Lech Szymanski:
VASE: Variational Assorted Surprise Exploration for Reinforcement Learning. CoRR abs/1910.14351 (2019) - [i8]Craig Atkinson, Brendan McCane, Lech Szymanski, Anthony V. Robins:
GRIm-RePR: Prioritising Generating Important Features for Pseudo-Rehearsal. CoRR abs/1911.11988 (2019) - 2018
- [j2]Brendan McCane, Lech Szymanski:
Efficiency of deep networks for radially symmetric functions. Neurocomputing 313: 119-124 (2018) - [c11]Haitao Xu, Brendan McCane, Lech Szymanski:
Twin Bounded Large Margin Distribution Machine. Australasian Conference on Artificial Intelligence 2018: 718-729 - [c10]Hannah Clark-Younger, Steven Mills, Lech Szymanski:
Stacked Hourglass CNN for Handwritten Character Location. IVCNZ 2018: 1-6 - [i7]Craig Atkinson, Brendan McCane, Lech Szymanski, Anthony V. Robins:
Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural Networks. CoRR abs/1802.03875 (2018) - [i6]Brendan McCane, Lech Szymanski:
Some Approximation Bounds for Deep Networks. CoRR abs/1803.02956 (2018) - [i5]Lech Szymanski, Brendan McCane, Michael H. Albert:
The effect of the choice of neural network depth and breadth on the size of its hypothesis space. CoRR abs/1806.02460 (2018) - [i4]Craig Atkinson, Brendan McCane, Lech Szymanski, Anthony V. Robins:
Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting. CoRR abs/1812.02464 (2018) - 2017
- [c9]Craig Atkinson, Brendan McCane, Lech Szymanski:
Increasing the accuracy of convolutional neural networks with progressive reinitialisation. IVCNZ 2017: 1-5 - [c8]Lech Szymanski, Steven Mills:
CNN for historic handwritten document search. IVCNZ 2017: 1-6 - [i3]Brendan McCane, Lech Szymanski:
Deep Radial Kernel Networks: Approximating Radially Symmetric Functions with Deep Networks. CoRR abs/1703.03470 (2017) - [i2]Lech Szymanski, Brendan McCane, Wei Gao, Zhi-Hua Zhou:
Effects of the optimisation of the margin distribution on generalisation in deep architectures. CoRR abs/1704.05646 (2017) - 2016
- [c7]Brendan McCane, Lech Szymanski:
Deep networks are efficient for circular manifolds. ICPR 2016: 3464-3469 - [d1]Xiping Fu, Brendan McCane, Steven Mills, Michael H. Albert, Lech Szymanski:
SIFT10M. UCI Machine Learning Repository, 2016
- [i1]Xiping Fu, Brendan McCane, Steven Mills, Michael H. Albert, Lech Szymanski:
Auto-JacoBin: Auto-encoder Jacobian Binary Hashing. CoRR abs/1602.08127 (2016) - 2014
- [j1]Lech Szymanski, Brendan McCane:
Deep Networks are Effective Encoders of Periodicity. IEEE Trans. Neural Networks Learn. Syst. 25(10): 1816-1827 (2014) - [c6]Steven Mills, Lech Szymanski, Reuben Johnson:
Hierarchical Structure from Motion from Endoscopic Video. IVCNZ 2014: 102 - 2013
- [c5]Lech Szymanski, Brendan McCane:
Learning in deep architectures with folding transformations. IJCNN 2013: 1-8 - [c4]Shawn Martin, Lech Szymanski:
Singularity resolution for dimension reduction. IVCNZ 2013: 19-24 - 2012
- [c3]Lech Szymanski, Brendan McCane:
Push-pull separability objective for supervised layer-wise training of neural networks. IJCNN 2012: 1-8 - [c2]Lech Szymanski, Brendan McCane:
Deep, super-narrow neural network is a universal classifier. IJCNN 2012: 1-8
2000 – 2009
- 2005
- [c1]Lech Szymanski, Martin Bouchard:
Comb filter decomposition for robust ASR. INTERSPEECH 2005: 2645-2648
Coauthor Index
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