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Found 4 papers, 3 papers with code
PMCE: efficient inference of expressive models of cancer evolution with high prognostic power
Motivation: Driver (epi)genomic alterations underlie the positive selection of cancer subpopulations, which promotes drug resistance and relapse.
Investigating the Compositional Structure Of Deep Neural Networks
By defining a direct acyclic graph representing the composition of activation patterns through the network layers, it is possible to characterize the instances of the input data with respect to both the predicted label and the specific (linear) transformation used to perform predictions.
OG-SPACE: Optimized Stochastic Simulation of Spatial Models of Cancer Evolution
We introduce the Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE), a computational framework for the simulation of the spatio-temporal evolution of cancer subpopulations and of the experimental procedures of both bulk andsingle-cell sequencing.
Unity is strength: Improving the Detection of Adversarial Examples with Ensemble Approaches
A key challenge in computer vision and deep learning is the definition of robust strategies for the detection of adversarial examples.
