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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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12243648 · Jun 202019922001200920172026
48 results for Almgren-Pitts width

The paper establishes a sub-additive inequality for volume and ε-phase-transition spectra of Riemannian manifolds.

problem Analyzing the volume and ε-phase-transition spectra of Riemannian manifolds.
method Using the Almgren-Pitts width and Allen-Cahn approach.
result Proves sub-additive inequalities for volume and ε-phase-transition spectra.

The volume spectrum of fiber bundles is bounded by the product of the base's volume spectrum and the fiber's volume.

problem Bounding the volume spectrum of fiber bundles and understanding its relationship with the base and fibers.
method Established an inequality relating the volume spectrum of a fiber bundle to the volume spectrum of its base and the volume of the largest fiber.
result The volume spectrum of a fiber bundle is bounded by the product of the volume spectrum of the base and the volume of the largest fiber.

The paper proves the existence of GG-invariant minimal hypersurfaces on certain Riemannian manifolds.

problem Existence of GG-invariant minimal hypersurfaces on specific Riemannian manifolds.
method Adapted Almgren-Pitts min-max theory to a GG-equivariant version.
result Existence of nontrivial closed smooth embedded GG-invariant minimal hypersurfaces.

I will talk about my recent work with Fernando Marques where we used Almgren-Pitts Min-max Theory to settle some open questions in Geometry: The Willmore conjecture, the Freedman-He-Wang conjecture for links (jointly with Ian Agol), and the existence of infinitely many minimal hypersurfaces in manifolds of positive Ric…

2014-09-26abs ↗pdf ↗

Proves existence of minimal surfaces with fixed boundary contact angle.

problem Existence of minimal surfaces with fixed boundary contact angle.
method Min-max construction in the spirit of Almgren-Pitts for the capillarity functional.
result Existence of minimal surfaces in a bounded convex subset of R^3 with fixed boundary contact angle.

In this paper, we study the shape of the min-max minimal hypersurface produced by Almgren-Pitts in \cite{A2}\cite{P} corresponding to the fundamental class of a Riemannian manifold (Mn+1,g)(M^{n+1}, g) of positive Ricci curvature with 2n62\leq n\leq 6. We characterize the Morse index, area and multiplicity of this min-max hyp…

2012-10-07abs ↗pdf ↗

We define the Wirtinger width of a knot. Then we prove the Wirtinger width of a knot equals its Gabai width. The algorithmic nature of the Wirtinger width leads to an efficient technique for establishing upper bounds on Gabai width. As an application, we use this technique to calculate the Gabai width of approximately …

2019-12-04abs ↗pdf ↗

Empirical study compares finite- and infinite-width BNNs, revealing performance differences under model mismatch.

problem Comparing BNNs with different widths due to conflicting model properties and inference intractability.
method Empirical comparison of finite- and infinite-width BNNs, analyzing performance under model mismatch.
result Increasing width can hurt BNN performance when the model is mis-specified, and finite-width BNNs generalize better under model mismatch.

The paper finds infinitely many half-volume CMC hypersurfaces on generic or Ricci-positive manifolds.

problem Finding infinitely many half-volume constant mean curvature (CMC) hypersurfaces on manifolds.
method Developed a min-max theory for non-local functionals to prove the existence of these hypersurfaces.
result Infinitely many geometrically distinct CMC hypersurfaces enclosing half the volume of a manifold.

Lectures on deep learning properties in infinite and large-width networks.

problem Understanding deep neural networks in extreme width conditions.
method Analysis of random deep neural networks, connections to linear models, kernels, and Gaussian processes, perturbative and non-perturbative treatments.
result Properties and behaviors of deep neural networks in the infinite-width limit and large-width regime.

A number of results for C2^2-smooth surfaces of constant width in Euclidean 3-space E3{\mathbb{E}}^3 are obtained. In particular, an integral inequality for constant width surfaces is established. This is used to prove that the ratio of volume to cubed width of a constant width surface is reduced by shrinking it along…

2007-04-24abs ↗pdf ↗

Residual networks with block width max(d_x, d_y) approximate all functions.

problem Achieving universal approximation with residual networks.
method Established bounds on block width for different activation functions.
result Minimum block width for universal approximation is max(d_x, d_y) with inner width 1.

While studying the existence of closed geodesics and minimal hypersurfaces in compact manifolds, the concept of width was introduced in different contexts. Generally, the width is realized by the energy of the closed geodesics or the volume of minimal hypersurfaces, which are found by the Minimax argument. Recently, Ma…

2016-12-20abs ↗pdf ↗

Study on Gaussian-width complexity on statistical manifolds and its applications in learning and recovery.

problem Understanding the geometry of statistical manifolds and its implications for learning and recovery.
method Analysis of Fisher width and inverse-Fisher width, proving their complementary roles and establishing a relation between them.
result Established a sharp relation between Fisher width and inverse-Fisher width, showing they cannot reduce relative to Euclidean scale.

Study infinite-depth limits of neural networks with fixed width.

problem Understanding the behavior of neural networks as depth increases with fixed width.
method Analyzing finite-width residual networks with random Gaussian weights, focusing on the infinite-depth limit.
result The pre-activations converge to a zero-drift diffusion process, differing from the infinite-width limit.

In "Width complexes for knots and 3-manifolds," Jennifer Schultens defines the width complex for a knot in order to understand the different positions a knot can occupy in the 3-sphere and the isotopies between these positions. She poses several questions about these width complexes; in particular, she asks whether the…

2010-08-30abs ↗pdf ↗

Wide neural networks can degrade performance, contrary to conventional wisdom.

problem Understanding the limitations of increasing network width in neural networks.
method Using Deep Gaussian Processes to decouple capacity and width, analyzing their effects on representational power and non-Gaussianity.
result Wide neural networks can become less adaptable and more Gaussian, leading to performance degradation.

We discuss a possible definition for "kk-width" of both a closed dd-manifold MdM^d, and on embedding MdeRnM^d \overset{e}{\hookrightarrow} \mathbb{R}^n, n>dkn > d \ge k, generalizing the classical notion of width of a knot. We show that for every 3-manifold 2-width(M3)2(M^3) \le 2 but that there are embeddings $e_i: T^3 \hoo…

2019-07-30abs ↗pdf ↗

The paper characterizes gaps in minimal foliations on tori using energy criteria.

problem Characterizing gaps in minimal foliations on tori.
method Introduced an energy to study min-max theory and applied it to Almgren-Pitts min-max theory.
result For a generic metric, if a lamination contains a gap, there exists a non-area-minimizing minimal hypersurface inside the gap.

We extend the classical definition of {\it width} to higher dimensional, smooth codimension 2 knots and show in each dimension there are knots of arbitrarily large width.

2019-02-19abs ↗pdf ↗

Self-attention models benefit equally from width and depth, but beyond a certain point, depth becomes less efficient.

problem Understanding the optimal balance between depth and width in self-attention models.
method Theoretical predictions and empirical ablations on networks of varying depths and widths.
result An optimal width of 30K is recommended for a 1-Trillion parameter network, marking a significant width for self-attention models.

We present an alternative proof of the following fact: the hyperspace of compact closed subsets of constant width in Rn\mathbb R^n is a contractible Hilbert cube manifold. The proof also works for certain subspaces of compact convex sets of constant width as well as for the pairs of compact convex sets of constant rela…

2004-01-07abs ↗pdf ↗

New framework for understanding infinite-width neural networks.

problem Understanding the infinite-width limit behavior of neural networks.
method General framework to study limit behavior of neural models based on hyperparameter scaling.
result Derives scaling for existing mean-field and neural tangent kernel limits and introduces new dynamically stable limits.

Wide CNNs outperform infinite width networks, revealing scaling laws.

problem Understanding the performance difference between finite and infinite width convolutional networks.
method Diagrammatic approach to derive asymptotic width dependence for various quantities.
result The difference in performance between finite and infinite width models vanishes at a definite rate with respect to model width.

Study examines dependence properties of Bayesian neural network units in finite-width networks.

problem Understanding dependence properties of hidden units in practical finite-width Bayesian neural networks.
method Theoretical analysis and empirical evaluation of depth and width impacts.
result Hidden units in finite-width Bayesian neural networks are dependent, contrary to the infinite-width limit assumption.