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Neural networks (NNs) are known for their high predictive accuracy in complex learning problems. Beside practical advantages, NNs also indicate favourable theoretical properties such as universal approximation (UA) theorems. Binarized…

Machine Learning · Computer Science 2021-02-05 Mikail Yayla , Mario Günzel , Burim Ramosaj , Jian-Jia Chen

We present a general variational framework for the training of freeform nonlinearities in layered computational architectures subject to some slope constraints. The regularization that we add to the traditional training loss penalizes the…

Machine Learning · Statistics 2025-03-31 Michael Unser , Alexis Goujon , Stanislas Ducotterd

We study multivariate polynomials over `structured' grids. We begin by proposing an interpretation as to what it means for a finite subset of a field to be structured; we do so by means of a numerical parameter, the nullity. We then extend…

Combinatorics · Mathematics 2023-11-17 Bogdan Nica

A net in $\mathbb{P}^2$ is a configuration of lines $\mathcal A$ and points $X$ satisfying certain incidence properties. Nets appear in a variety of settings, ranging from quasigroups to combinatorial design to classification of Kac-Moody…

Combinatorics · Mathematics 2022-09-20 Nancy Abdallah , Hal Schenck

Observable structures of a topological field theory of AKSZ type are analyzed. From a double (or multiple) complex structure of observable algebras, new topological invariants are constructed. Especially, Donaldson polynomial invariants and…

High Energy Physics - Theory · Physics 2011-04-13 Noriaki Ikeda

We provide a general approach to Lipschitz regularity of solutions for a large class of vector-valued, nonautonomous variational problems exhibiting nonuniform ellipticity. The functionals considered here range amongst those with unbalanced…

Analysis of PDEs · Mathematics 2021-08-02 Cristiana De Filippis , Giuseppe Mingione

The derived group of a permutation representation, introduced by R.H. Crowell, unites many notions of knot theory. We survey Crowell's construction, and offer new applications. The twisted Alexander group of a knot is defined. Using it, we…

Geometric Topology · Mathematics 2007-05-23 Daniel S. Silver , Susan G. Williams

A celebrated result in bifurcation theory is that global connected sets of non-trivial solutions bifurcate from trivial solutions at non-zero eigenvalues of odd algebraic multiplicity of the linearized problem when the operators involved…

Analysis of PDEs · Mathematics 2021-04-12 J. F. Toland

We show that the Hrushovski-\fraisse limit of certain classes of trees lead to strictly superstable theories of various U-ranks. In fact, for each $ \alpha\in\omega+1\backslash\{0\} $ we introduce a strictly superstable theory of U-rank $…

Logic · Mathematics 2025-10-16 Ali N. Valizadeh , Massoud Pourmahdian

We prove the invariance of plurigenera under smooth projective deformations in full generality. The proof is done by several estimates of singular hermitian metrics in terms of $L^{2}$-extension theorem of holomorphic sections.

Algebraic Geometry · Mathematics 2007-05-23 Hajime Tsuji

We describe methods for calculation of polytopes of quasiadjunction for plane curve singularities which are invariants giving a Hodge theoretical refinement of the zero sets of multivariable Alexander polynomials. In particular we identify…

Algebraic Geometry · Mathematics 2009-04-08 Pierrette Cassou-Nogues , Anatoly Libgober

We study the diversity of the features learned by a two-layer neural network trained with the least squares loss. We measure the diversity by the average $L_2$-distance between the hidden-layer features and theoretically investigate how…

Machine Learning · Computer Science 2023-06-14 Firas Laakom , Jenni Raitoharju , Alexandros Iosifidis , Moncef Gabbouj

We consider here operators which are sum of (possibly) fractional derivatives, with (possibly different) order. The main constructive assumption is that the operator is of order~$2$ in one variable. By constructing an explicit barrier, we…

Analysis of PDEs · Mathematics 2016-09-22 Alberto Farina , Enrico Valdinoci

We provide a full characterisation of all of the possible alternating group ($A_n$) equivariant neural networks whose layers are some tensor power of $\mathbb{R}^{n}$. In particular, we find a basis of matrices for the learnable, linear,…

Machine Learning · Computer Science 2023-06-21 Edward Pearce-Crump

In this paper, we consider the problem of minimizing a linear functional subject to uncertain linear and bilinear matrix inequalities, which depend in a possibly nonlinear way on a vector of uncertain parameters. Motivated by recent results…

Optimization and Control · Mathematics 2015-05-29 Mohammadreza Chamanbaz , Fabrizio Dabbene , Roberto Tempo , Venkatakrishnan Venkataramanan , Qing-Guo Wang

As an application of P. Delgine's theorem (Esnault and Kerz in Acta Math. Vietnam. 37:531-562, 2012) on a finiteness of $l$-adic sheaves on a variety over a finite field, we show the finiteness of \'etale coverings of such a variety with…

Number Theory · Mathematics 2016-12-12 Toshiro Hiranouchi

In this paper we present a sequence of link invariants, defined from twisted Alexander polynomials, and discuss their effectiveness in distinguish knots. In particular, we recast and extend by geometric means a recent result of Silver and…

Geometric Topology · Mathematics 2018-12-24 Stefan Friedl , Stefano Vidussi

The aim of this paper is to summarize some recently obtained relations between the Ablowitz-Ladik hierarchy (ALH) and other integrable equations. It has been shown that solutions of finite subsystems of the ALH can be used to derive a wide…

solv-int · Physics 2007-05-23 V. E. Vekslerchik

We generalize the classical study of Alexander polynomials of smooth or PL locally-flat knots to PL knots that are not necessarily locally-flat. We introduce three families of generalized Alexander polynomials and study their properties.…

Geometric Topology · Mathematics 2011-03-31 Greg Friedman

Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems. Taking the perspective of synthesizing graph theory programs,…

Machine Learning · Computer Science 2020-10-27 Hao Tang , Zhiao Huang , Jiayuan Gu , Bao-Liang Lu , Hao Su