Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks

Deep neural networks have emerged as a widely used and effective means for tackling complex, real-world problems. However, a major obstacle in applying them to safety-critical systems is the great difficulty in providing formal guarantees about their behavior. We present a novel, scalable, and efficient technique for verifying properties of deep neural networks (or providing counter-examples). The technique is based on the simplex method, extended to handle the non-convex Rectified Linear Unit (ReLU) activation function, which is a crucial ingredient in many modern neural networks. The verification procedure tackles neural networks as a whole, without making any simplifying assumptions. We evaluated our technique on a prototype deep neural network implementation of the next-generation airborne collision avoidance system for unmanned aircraft (ACAS Xu). Results show that our technique can successfully prove properties of networks that are an order of magnitude larger than the largest networks verified using existing methods.Comment: This is the extended version of a paper with the same title that appeared at CAV 201

Integrated Structure and Semantics for Reo Connectors and Petri Nets

In this paper, we present an integrated structural and behavioral model of Reo connectors and Petri nets, allowing a direct comparison of the two concurrency models. For this purpose, we introduce a notion of connectors which consist of a number of interconnected, user-defined primitives with fixed behavior. While the structure of connectors resembles hypergraphs, their semantics is given in terms of so-called port automata. We define both models in a categorical setting where composition operations can be elegantly defined and integrated. Specifically, we formalize structural gluings of connectors as pushouts, and joins of port automata as pullbacks. We then define a semantical functor from the connector to the port automata category which preserves this composition. We further show how to encode Reo connectors and Petri nets into this model and indicate applications to dynamic reconfigurations modeled using double pushout graph transformation

Unbiased Global Optimization of Lennard-Jones Clusters for N <= 201 by Conformational Space Annealing Method

We apply the conformational space annealing (CSA) method to the Lennard-Jones clusters and find all known lowest energy configurations up to 201 atoms, without using extra information of the problem such as the structures of the known global energy minima. In addition, the robustness of the algorithm with respect to the randomness of initial conditions of the problem is demonstrated by ten successful independent runs up to 183 atoms. Our results indicate that the CSA method is a general and yet efficient global optimization algorithm applicable to many systems.Comment: revtex, 4 pages, 2 figures. Physical Review Letters, in pres

Minimizing the stabbing number of matchings, trees, and triangulations

The (axis-parallel) stabbing number of a given set of line segments is the maximum number of segments that can be intersected by any one (axis-parallel) line. This paper deals with finding perfect matchings, spanning trees, or triangulations of minimum stabbing number for a given set of points. The complexity of these problems has been a long-standing open question; in fact, it is one of the original 30 outstanding open problems in computational geometry on the list by Demaine, Mitchell, and O'Rourke. The answer we provide is negative for a number of minimum stabbing problems by showing them NP-hard by means of a general proof technique. It implies non-trivial lower bounds on the approximability. On the positive side we propose a cut-based integer programming formulation for minimizing the stabbing number of matchings and spanning trees. We obtain lower bounds (in polynomial time) from the corresponding linear programming relaxations, and show that an optimal fractional solution always contains an edge of at least constant weight. This result constitutes a crucial step towards a constant-factor approximation via an iterated rounding scheme. In computational experiments we demonstrate that our approach allows for actually solving problems with up to several hundred points optimally or near-optimally.Comment: 25 pages, 12 figures, Latex. To appear in "Discrete and Computational Geometry". Previous version (extended abstract) appears in SODA 2004, pp. 430-43

Specific fibroblast subpopulations and neuronal structures provide local sources of Vegfc-processing components during zebrafish lymphangiogenesis

Proteolytical processing of the growth factor VEGFC through the concerted activity of CCBE1 and ADAMTS3 is required for lymphatic development to occur. How these factors act together in time and space, and which cell types produce these factors is not understood. Here we assess the function of Adamts3 and the related protease Adamts14 during zebrafish lymphangiogenesis and show both proteins to be able to process Vegfc. Only the simultaneous loss of both protein functions results in lymphatic defects identical to vegfc loss-of-function situations. Cell transplantation experiments demonstrate neuronal structures and/or fibroblasts to constitute cellular sources not only for both proteases but also for Ccbe1 and Vegfc. We further show that this locally restricted Vegfc maturation is needed to trigger normal lymphatic sprouting and directional migration. Our data provide a single-cell resolution model for establishing secretion and processing hubs for Vegfc during developmental lymphangiogenesis

Early onset facioscapulohumeral dystrophy - a systematic review using individual patient data

Infantile or early onset is estimated to occur in around 10% of all facioscapulohumeral dystrophy (FSHD) patients. Although small series of early onset FSHD patients have been reported, comprehensive data on the clinical phenotype is missing. We performed a systematic literature search on the clinical features of early onset FSHD comprising a total of 43 articles with individual data on 227 patients. Additional data from four cohorts was provided by the authors. Mean age at reporting was 18.8 years, and 40% of patients were wheelchair-dependent at that age. Half of the patients had systemic features, including hearing loss (40%), retinal abnormalities (37%) and developmental delay (8%). We found an inverse correlation between repeat size and disease severity, similar to adult-onset FSHD. De novo FSHD1 mutations were more prevalent than in adult-onset FSHD. Compared to adult FSHD, our findings indicate that early onset FSHD is overall characterized by a more severe muscle phenotype and a higher prevalence of systemic features. However, similar as in adults, a significant clinical heterogeneity was observed. Based on this, we consider early onset FSHD to be on the severe end of the FSHD disease spectrum. We found natural history studies and treatment studies to be very scarce in early onset FSHD, therefore longitudinal studies are needed to improve prognostication, clinical management and trial-readiness

Editor's Choice \u2013 Management of Atherosclerotic Carotid and Vertebral Artery Disease: 2017 Clinical Practice Guidelines of the European Society for Vascular Surgery (ESVS)

2017 Clinical Practice Guidelines of the European Society for Vascular Surgery