constraint abstractions into integer programming, and to discuss possible combinations of the two approaches. Combinatorial problems are ubiquitous in many real world applications ...
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
— In this paper we address the problem of predicting gene activities by finding gene regulatory dependencies in experimental DNA microarray data. Only few approaches to infer th...
Christian Spieth, Felix Streichert, Nora Speer, Ch...
In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...