Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2024; 33rd International C Michael Wand,Kristína Malinovská,Igor V. Tetko Conferenc

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Maria Michaelidou M. D.,Manfred Freyistributions using Langevin dynamics in the VSA vector space, and demonstrate competitive sampling performance in a spiking-neural network implementation. Surprisingly, while the Langevin dynamics are not constrained to the manifold defined by the HRR encoding, the generated samples contain sufficie

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Kathryn L. Butler,Robert L. Sheridanaptive learning behavior is represented through a microcircuit centered around a variable resistor. We validated the model’s efficacy in storing and retrieving data through computer simulations. This approach offers a plausible biological explanation for memory realization and validates the memory t

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Kunaal Jindal,Shahriar Shahrokhistimation of the storage capacity of memory NNs is crucial, as there is a limitation to the quantity of information that a finite NN can store and retrieve correctly. The storage capacity of the Hopfield associative memory model has been estimated to be proportional to the number of neurons in the n

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意外的成功

Leopoldo C. Cancio,Jonathan B. Lundyimizing the impact of irrelevant context feature and purifying the feature space for more precise classification. We validate our model on CUB-200-2011, Stanford Cars, and WM-811K datasets. Both accuracy and robustness are significantly improved, which demonstrate notable improvements in accuracy an

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Leopoldo C. Cancio,Steven E. Wolfage counterfactual explanations. Our experiments demonstrate that the counterfactual explanations generated by our method closely resemble the original images in both pixel and feature spaces. Additionally, our method outperforms established baselines, achieving impressive experimental results.

sclera

https://doi.org/10.1007/978-3-030-18940-2d the other for gender classification and sentiment analysis. Notably, the results reveal that the removal of gender-related dimensions significantly affects gender classification performance while having minimal impact on other tasks. This highlights that there exist different related dimensions fo

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A Multiscale Resonant Spiking Neural Network for?Music Classificationobile devices becoming the dominant approaches to music, the light weight and mobile deployabiliy of music classification models are also of growing importance. Artificial Neural Networks(ANNs) have been the mainstream paradigms for music classification, but problems concerning with computational an