Every homomorphism from finite index subgroups of a universal lattices to mapping class groups of orientable surfaces (possibly with punctures), or to outer automorphism groups of finitely generated nonabelian free groups must have finite image. Here the universal lattice denotes the special linear group G=SL_m(Z[x1,..…
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Narasihman and Ramanan proved that an arbitrary connection in a vector bundle over a base space B can be obtained as the pull-back (via a correctly chosen classifying map from B into the appropriate Grassmannian) of the universal connection in the universal bundle over the Grassmannian. The purpose of this paper is to …
Universal approximation for ODENet and ResNet with a single activation function.
The paper defines a universal Teichmüller space for PGL_d(R) and proves its properties.
NODEs can approximate a wide range of diffeomorphisms with strong guarantees.
Effective feature representation is key to the predictive performance of any algorithm. This paper introduces a meta-procedure, called Non-Euclidean Upgrading (NEU), which learns feature maps that are expressive enough to embed the universal approximation property (UAP) into most model classes while only outputting fea…
The aim of this paper is to introduce the concepts of homotopical smallness and closeness. These are the properties of homotopical classes of maps that are related to recent developments in homotopy theory and to the construction of universal covering spaces for non-semilocally simply connected spaces, in particular to…
A new category generates 1D tangle invariants.
For several instances of metric largeness like enlargeability or having hyperspherical universal covers, we construct non-large vector subspaces in the rational homology of finitely generated groups. The functorial properties of this construction imply that the corresponding largeness properties of closed manifolds dep…
Quantum machine learning models can approximate any continuous function.
Unified theorem for deep and shallow joint-equivariant machines.
Path signatures adapted for Lie groups improve action recognition in computer vision.
Starting from ideas of Furuta, we develop a general formalism for the construction of cohomotopy invariants associated with a certain class of -equivariant non-linear maps between Hilbert bundles. Applied to the Seiberg-Witten map, this formalism yields a new class of cohomotopy Seiberg-Witten invariants which hav…
An alternate proof shows how foliation extensions work in 3D spaces.
New maps connect universal circles to ideal sphere for hyperbolic manifolds.
Starting from an arbitrary sequence of polygons whose total perimeter is , we can build an (oriented) surface by pairing their sides in a uniform fashion. Chmutov and Pittel (arXiv:1503.01816) have shown that, regardless of the configuration of polygons we started with, the degree sequence of the graph obtained thi…
Constructs a universal Cannon-Thurston map for a new curve complex.
Let be a compact complex manifold with trivial canonical bundle and satisfying the -Lemma. We show that the Kuranishi space of is a smooth universal deformation and that small deformations enjoy the same properties as . If, in addition, admits a complex symplectic form, then the l…
Dimension reduction is the process of embedding high-dimensional data into a lower dimensional space to facilitate its analysis. In the Euclidean setting, one fundamental technique for dimension reduction is to apply a random linear map to the data. This dimension reduction procedure succeeds when it preserves certain …
We present effective methods to compute equivariant harmonic maps from the universal cover of a surface into a nonpositively curved space. By discretizing the theory appropriately, we show that the energy functional is strongly convex and derive convergence of the discrete heat flow to the energy minimizer, with explic…
Real blow-up, including inhomogeneous versions, of boundary faces of a manifold (with corners) is an important tool for resolving singularities, degeneracies and competing notions of homogeneity. These constructions are shown to be particular cases of `generalized boundary blow-up' in which a new manifold and blow-down…
We extend the notion of an almost flat bundle over a closed Riemannian manifold to bundles over simplicial complexes, and prove that up to a constant factor, this notion is invariant under pullback via maps which induce isomorphisms on fundamental groups. As an application, we show that the property of having infinite …
The paper shows that for Coxeter groups, the commensurator of outer automorphisms is rigid.
Unified method for CNNs to approximate equivariant maps across various groups.
We give chain homotopy maps of Khovanov-type link homology of a universal differential. The universal differential, discussed by Mikhail Khovanov, Marco Mackaay, Paul Turner and Pedro Vaz, contains the original Khovanov's differential and Lee's differential. We also consider the conditions of any differential ensuring …
Study geometric properties of log Calabi-Yau manifolds, focusing on Fano manifolds with smooth or two proportional components.
Universal approximation theorem for differentiable maps on infinite-dimensional manifolds
Identifies holonomy of affine surfaces via meromorphic connections.
We prove the universal lifting theorem: for an -simply connected and -connected Lie groupoid $\gm$ with Lie algebroid , the graded Lie algebra of multi-differentials on is isomorphic to that of multiplicative multi-vector fields on $\gm$. As a consequence, we obtain the integration theorem for a quasi-Lie …
This paper establishes rates of universal approximation for the shallow neural tangent kernel (NTK): network weights are only allowed microscopic changes from random initialization, which entails that activations are mostly unchanged, and the network is nearly equivalent to its linearization. Concretely, the paper has …
We study the approximation properties of random ReLU features through their reproducing kernel Hilbert space (RKHS). We first prove a universality theorem for the RKHS induced by random features whose feature maps are of the form of nodes in neural networks. The universality result implies that the random ReLU features…
Despite the widespread adoption of Transformer models for NLP tasks, the expressive power of these models is not well-understood. In this paper, we establish that Transformer models are universal approximators of continuous permutation equivariant sequence-to-sequence functions with compact support, which is quite surp…
This short review is the result of a minicourse at the Sapienza University of Rome the author gave about the proof of the -theorem. We review the hard Lefschetz theorem for simplicial spheres, as well as the theory at its core: perturbations of maps, biased Poincaré pairings and a cobordism argument that relates the…
Universal spaces for finite topological spaces simplify shape descriptions.
New proof shows incremental flow models are essential for universal generation.
The paper defines a condition for the finiteness of mapping class groups of Heegaard splittings.
The paper discusses -deformations of the Aomoto complex.
Assume that all spaces and maps are localised at a fixed prime . We study the possibility of generating a universal space from a space which is universal in the category of homotopy associative, homotopy commutative H-spaces in the sense that any map f:X->Y to a homotopy associative, homotopy commutative …
New theory maps spin structures on surfaces, generating key elements.
We introduce a new feature map for barcodes that arise in persistent homology computation. The main idea is to first realize each barcode as a path in a convenient vector space, and to then compute its path signature which takes values in the tensor algebra of that vector space. The composition of these two operations …
Metric spaces with certain curvature properties are universally infinitesimally Hilbertian.
Generalizes neural network approximation to infinite-dimensional manifolds and derivatives.
Learning three data points can generate all types of periodic orbits in a neural network.
Introduces a new method for symplectic reduction along submanifolds.
Geometric approach to moment maps in complex geometry.
Universal Gaussian parity proven for 2D knots.
A basic problem in machine learning is to find a mapping from a low dimensional latent space to a high dimensional observation space . Modern tools such as deep neural networks are capable to represent general non-linear mappings. A learner can easily find a mapping which perfectly fits a…
We record various properties of twisted Becker-Gottlieb transfer maps and study their multiplicative properties analogous to Becker-Gottlieb transfer. We show these twisted transfer maps factorise through Becker-Schultz-Mann-Miller-Miller transfer; some of these might be well known. We apply this to show that $BSO(2n+1…