Romanian Academy

About: Romanian Academy is a archive organization based out in Bucharest, Romania. It is known for research contribution in the topics: Population & Nonlinear system. The organization has 3662 authors who have published 10491 publications receiving 146447 citations. The organization is also known as: Academia Română & Societatea Literară Română.

Deep Learning of Graph Matching

Abstract: The problem of graph matching under node and pairwise constraints is fundamental in areas as diverse as combinatorial optimization, machine learning or computer vision, where representing both the relations between nodes and their neighborhood structure is essential. We present an end-to-end model that makes it possible to learn all parameters of the graph matching process, including the unary and pairwise node neighborhoods, represented as deep feature extraction hierarchies. The challenge is in the formulation of the different matrix computation layers of the model in a way that enables the consistent, efficient propagation of gradients in the complete pipeline from the loss function, through the combinatorial optimization layer solving the matching problem, and the feature extraction hierarchy. Our computer vision experiments and ablation studies on challenging datasets like PASCAL VOC keypoints, Sintel and CUB show that matching models refined end-to-end are superior to counterparts based on feature hierarchies trained for other problems.

Jet schemes of locally complete intersection canonical singularities

Abstract: Let X be a variety defined over an algebraically closed field k of characteristic zero The mth jet scheme Xm of X is a scheme whose closed points over x ∈ X are morphisms OX,x −→ k[t]/(tm+1) When X is a smooth variety, this is an affine bundle over X, of dimension (m + 1) dim X The space of arcs X∞ of X is the projective limit X∞ = proj limm Xm Our main result is a proof of the following theorem, which was conjectured by Eisenbud and Frenkel:

Munc13-4 is an effector of rab27a and controls secretion of lysosomes in hematopoietic cells.

Abstract: Griscelli syndrome type 2 (GS2) is a genetic disorder in which patients exhibit life-threatening defects of cytotoxic T lymphocytes (CTLs) whose lytic granules fail to dock on the plasma membrane and therefore do not release their contents. The disease is caused by the absence of functional rab27a, but how rab27a controls secretion of lytic granule contents remains elusive. Mutations in Munc13-4 cause familial hemophagocytic lymphohistiocytosis subtype 3 (FHL3), a disease phenotypically related to GS2. We show that Munc13-4 is a direct partner of rab27a. The two proteins are highly expressed in CTLs and mast cells where they colocalize on secretory lysosomes. The region comprising the Munc13 homology domains is essential for the localization of Munc13-4 to secretory lysosomes. The GS2 mutant rab27aW73G strongly reduced binding to Munc13-4, whereas the FHL3 mutant Munc13-4Δ608-611 failed to bind rab27a. Overexpression of Munc13-4 enhanced degranulation of secretory lysosomes in mast cells, showing that it has a positive regulatory role in secretory lysosome fusion. We suggest that the secretion defects seen in GS2 and FHL3 have a common origin, and we propose that the rab27a/Munc13-4 complex is an essential regulator of secretory granule fusion with the plasma membrane in hematopoietic cells. Mutations in either of the two genes prevent formation of this complex and abolish secretion.

A survey of applications of the MFS to inverse problems

Abstract: The method of fundamental solutions (MFS) is a relatively new method for the numerical solution of boundary value problems and initial/boundary value problems governed by certain partial differential equations. The ease with which it can be implemented and its effectiveness have made it a very popular tool for the solution of a large variety of problems arising in science and engineering. In recent years, it has been used extensively for a particular class of such problems, namely inverse problems. In this study, in view of the growing interest in this area, we review the applications of the MFS to inverse and related problems, over the last decade.