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Found 8 papers, 0 papers with code
A cross-study analysis of drug response prediction in cancer cell lines
To provide a more rigorous assessment of model generalizability between different studies, we use machine learning to analyze five publicly available cell line-based data sets: NCI60, CTRP, GDSC, CCLE and gCSI.
Uncertainty Bounds for Multivariate Machine Learning Predictions on High-Strain Brittle Fracture
Simulation of the crack network evolution on high strain rate impact experiments performed in brittle materials is very compute-intensive.
Convolutional Dictionary Learning: A Comparative Review and New Algorithms
Convolutional sparse representations are a form of sparse representation with a dictionary that has a structure that is equivalent to convolution with a set of linear filters.
First and Second Order Methods for Online Convolutional Dictionary Learning
Convolutional sparse representations are a form of sparse representation with a structured, translation invariant dictionary.
Online Convolutional Dictionary Learning
While a number of different algorithms have recently been proposed for convolutional dictionary learning, this remains an expensive problem.
Multiclass Semi-Supervised Learning on Graphs using Ginzburg-Landau Functional Minimization
We present a graph-based variational algorithm for classification of high-dimensional data, generalizing the binary diffuse interface model to the case of multiple classes.
Spectral Clustering with Epidemic Diffusion
Existing methods for spectral clustering use the eigenvalues and eigenvectors of the graph Laplacian, an operator that is closely associated with random walks on graphs.
Multiclass Data Segmentation using Diffuse Interface Methods on Graphs
We present two graph-based algorithms for multiclass segmentation of high-dimensional data.
