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Revealing the Excitation Causality between Climate and Political Violence via a Neural Forward-Intensity Poisson Process
The causal mechanism between climate and political violence is fraught with complex mechanisms.
Scarce Data Driven Deep Learning of Drones via Generalized Data Distribution Space
We believe that this approach of exploiting general data distribution knowledge form neural networks can be applied to a wide range of scarce data open challenges.
Scalable Partial Explainability in Neural Networks via Flexible Activation Functions
In this paper, we achieve partially explainable learning model by symbolically explaining the role of activation functions (AF) under a scalable topology.
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