3 accepted papers
Unlike their biological counterparts, simple artificial neural networks are unable to retain information from their past state to influence their behavior. In this contribution, we propose to consider new nonlinear activation functions, whose outputs depend both from the current and past inputs thro…
As field seismic data sizes are dramatically increasing toward exabytes, automating the labeling of “structural monads” - corresponding to geological patterns and yielding subsurface interpretation - in a huge amount of available information would drastically reduce interpretation time. Since custom…
With the advent of microarrays, arose the need to analyze gene expression data. Tools for building gene regulation networks are indeed of high interest for regulatory relationship sketching and gene interaction prediction. Given all pairwise gene regulation information available, we propose to deter…