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We show that standard machine-learning algorithms may be trained to predict certain invariants of low genus arithmetic curves. Using datasets of size around one hundred thousand, we demonstrate the utility of machine-learning in…

Number Theory · Mathematics 2023-07-14 Yang-Hui He , Kyu-Hwan Lee , Thomas Oliver

Oblique images are aerial photographs taken at oblique angles to the earth's surface. Projections of vector and other geospatial data in these images depend on camera parameters, positions of the geospatial entities, surface terrain,…

Computer Vision and Pattern Recognition · Computer Science 2022-06-22 Pragyana Mishra , Eyal Ofek , Gur Kimchi

We present novel graph kernels for graphs with node and edge labels that have ordered neighborhoods, i.e. when neighbor nodes follow an order. Graphs with ordered neighborhoods are a natural data representation for evolving graphs where…

Machine Learning · Computer Science 2018-05-30 Moez Draief , Konstantin Kutzkov , Kevin Scaman , Milan Vojnovic

Sweeping is a powerful and versatile method of designing objects. Boundary of volumes (henceforth envelope) obtained by sweeping solids have been extensively investigated in the past, though, obtaining an accurate parametrization of the…

Other Computer Science · Computer Science 2012-04-05 Bharat Adsul , Jinesh Machchhar , Milind Sohoni

Deep neural networks can be trained to be efficient and effective controllers for dynamical systems; however, the mechanics of deep neural networks are complex and difficult to guarantee. This work presents a general approach for providing…

Systems and Control · Computer Science 2019-06-05 Kyle D. Julian , Mykel J. Kochenderfer

Understanding properties of deep neural networks is an important challenge in deep learning. In this paper, we take a step in this direction by proposing a rigorous way of verifying properties of a popular class of neural networks,…

Machine Learning · Statistics 2018-06-04 Nina Narodytska , Shiva Prasad Kasiviswanathan , Leonid Ryzhyk , Mooly Sagiv , Toby Walsh

We use machine learning to classify examples of braids (or flat braids) as trivial or non-trivial. Our ML takes form of supervised learning using neural networks (multilayer perceptrons). When they achieve good results in classification, we…

Geometric Topology · Mathematics 2023-07-25 Alexei Lisitsa , Mateo Salles , Alexei Vernitski

Deep neural networks (DNNs) are widely used in real-world applications, yet they remain vulnerable to errors and adversarial attacks. Formal verification offers a systematic approach to identify and mitigate these vulnerabilities, enhancing…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Yizhak Y. Elboher , Avraham Raviv , Yael Leibovich Weiss , Omer Cohen , Roy Assa , Guy Katz , Hillel Kugler

Two curves are affinely equivalent if there exists an affine mapping transforming one of them onto the other. Thus, detecting affine equivalence comprises, as important particular cases, similarity, congruence and symmetry detection. In…

Algebraic Geometry · Mathematics 2024-03-27 Juan Gerardo Alcázar , Hüsnü Anıl Çoban , Uğur Gözütok

Image tracing is a foundational component of the workflow in graphic design, engineering, and computer animation, linking hand-drawn concept images to collections of smooth curves needed for geometry processing and editing. Even for clean…

Graphics · Computer Science 2018-09-07 Mikhail Bessmeltsev , Justin Solomon

Tightness is a generalisation of the notion of convexity: a space is tight if and only if it is "as convex as possible", given its topological constraints. For a simplicial complex, deciding tightness has a straightforward exponential time…

Computational Geometry · Computer Science 2018-10-24 Bhaskar Bagchi , Benjamin A. Burton , Basudeb Datta , Nitin Singh , Jonathan Spreer

Let X be a (possibly nodal) K-trivial threefold moving in a fixed ambient space P. Suppose X contains a continuous family of curves, all of whose members satisfy certain unobstructedness conditions in P. A formula is given for computing the…

Algebraic Geometry · Mathematics 2007-05-23 Herbert Clemens , Holger P. Kley

Deep neural networks are revolutionizing the way complex systems are developed. However, these automatically-generated networks are opaque to humans, making it difficult to reason about them and guarantee their correctness. Here, we propose…

Artificial Intelligence · Computer Science 2020-08-11 Yuval Jacoby , Clark Barrett , Guy Katz

Binary classification problems can be naturally modeled as bipartite graphs, where we attempt to classify right nodes based on their left adjacencies. We consider the case of labeled bipartite graphs in which some labels and edges are not…

Combinatorics · Mathematics 2018-11-13 R. W. R. Darling , Mark L. Velednitsky

Mapper is an unsupervised machine learning algorithm generalising the notion of clustering to obtain a geometric description of a dataset. The procedure splits the data into possibly overlapping bins which are then clustered. The output of…

Algebraic Topology · Mathematics 2019-06-05 Francisco Belchí , Jacek Brodzki , Matthew Burfitt , Mahesan Niranjan

We present an algorithm for detecting basepoints of linear series of curves in the plane. Moreover, we give an algorithm for constructing a linear series of curves in the plane for given basepoints. The underlying method of these algorithms…

Algebraic Geometry · Mathematics 2018-05-10 Niels Lubbes

In this paper we introduce an algorithm of construction of cyclic space-filling curves. One particular construction provides a family of space-filling curves in all dimensions (H-curves). They are compared here with the Hilbert curve in the…

Data Structures and Algorithms · Computer Science 2020-06-19 Igor V. Netay

In this paper we describe a new technique to generate and use surfels for rendering of highly complex, polygonal 3D scenes in real time. The basic idea is to approximate complex parts of the scene by rendering a set of points (surfels). The…

Graphics · Computer Science 2013-07-02 Claudius Jähn

As machine learning systems are increasingly used to make real world legal and financial decisions, it is of paramount importance that we develop algorithms to verify that these systems do not discriminate against minorities. We design a…

Artificial Intelligence · Computer Science 2020-01-01 Osbert Bastani , Xin Zhang , Armando Solar-Lezama

Formally verifying properties of programs that manipulate arrays in loops is computationally challenging. In this paper, we focus on a useful class of such programs, and present a novel property-driven verification method that first infers…

Software Engineering · Computer Science 2017-10-05 Supratik Chakraborty , Ashutosh Gupta , Divyesh Unadkat