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06/21/2023
Efficient Deep Spiking Multi-Layer Perceptrons with Multiplication-Free Inference
Advancements in adapting deep convolution architectures for Spiking Neur...
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04/18/2020
A Large Dataset of Historical Japanese Documents with Complex Layouts
Deep learning-based approaches for automatic document layout analysis an...
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11/12/2019
Connecting First and Second Order Recurrent Networks with Deterministic Finite Automata
We propose an approach that connects recurrent networks with different o...
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10/15/2019
Shapley Homology: Topological Analysis of Sample Influence for Neural Networks
Data samples collected for training machine learning models are typicall...
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11/14/2018
Verification of Recurrent Neural Networks Through Rule Extraction
The verification problem for neural networks is verifying whether a neur...
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01/16/2018
A Comparison of Rule Extraction for Different Recurrent Neural Network Models and Grammatical Complexity
It has been shown that rules can be extracted from highly non-linear, re...
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05/23/2017