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.
Conformer encoder reverses sequence in time dimension, affecting decoder training.
HR in 8D encodes unique conformal gravity with negative curvature.
Motivation: Proteins are known to undergo conformational changes in the course of their functions. The changes in conformation are often attributable to a small fraction of residues within the protein. Therefore identification of these variable regions is important for an understanding of protein function. Results: We …
This paper proposes grid cells encode position via a conformal isometric embedding of 2D physical space.
In this review, we collect several results for conformally standard stationary spacetimes (SxR,g) obtained in terms of a Finsler metric of Randers type on the orbit manifold S that we call Fermat metric. This metric is obtained by applying the relativistic Fermat principle and it turns out that it encodes all the causa…
We consider a triality between the Zermelo navigation problem, the geodesic flow on a Finslerian geometry of Randers type, and spacetimes in one dimension higher admitting a timelike conformal Killing vector field. From the latter viewpoint, the data of the Zermelo problem are encoded in a (conformally) Painleve-Gullst…
The paper proves a rigidity theorem for null geodesic travel times in asymptotically AdS spacetimes.
New boundary and point constraints for controlling conformal surfaces.
SPLICE generates accurate time-series imputations with reliable prediction intervals.
Extend CPS to non-exchangeable settings with observation-specific permutation weights
The structure of a Frobenius manifold encodes the geometry associated with a flat pencil of metrics. However, as shown in the authors' earlier work, much of the structure comes from the compatibility properties of the pencil rather than from the flatness of the pencil itself. In this paper conformally flat pencils of m…
New conformal geometry method solves Einstein-Weyl equations.
We study the relations between the projective and the almost conformally symplectic structures on a smooth even dimensional manifold. We describe these relations by a single almost conformally symplectic connection with totally trace--free torsion sharing the geodesics (up to parametrization) with the projective class.…
Study examines flaws in probing LLMs' knowledge and introduces a new method.
Study on Yang-Mills equations on conformally compact manifolds, finding obstructions and asymptotics.
Quaternion Conformer GAN (QC-GAN) is a parameter-efficient speech enhancement framework that combines a Quaternion Conformer generator with MetricGAN-based training.
This work connects conformal prediction to information theory for uncertainty estimation.
LoBoost improves local conformal prediction for gradient-boosted trees without extra data splits.
We study higher form Proca equations on Einstein manifolds with boundary data along conformal infinity. We solve these Laplace-type boundary problems formally, and to all orders, by constructing an operator which projects arbitrary forms to solutions. We also develop a product formula for solving these asymptotic probl…
Conformal geodesics are distinguished curves on a conformal manifold, loosely analogous to geodesics of Riemannian geometry. One definition of them is as solutions to a third order differential equation determined by the conformal structure. There is an alternative description via the tractor calculus. In this article …
New operators and curvatures derived from embedded manifolds.
ICP improves text infilling and POS tagging with valid confidence sets.
The paper generalizes Farey tessellation to 3D hyperbolic space.
As deep Variational Auto-Encoder (VAE) frameworks become more widely used for modeling biomolecular simulation data, we emphasize the capability of the VAE architecture to concurrently maximize the timescale of the latent space while inferring a reduced coordinate, which assists in finding slow processes as according t…
New tractor geometry derived from asymptotically flat spacetimes.
Conformal Autoencoders infer intrinsic dimensionality and impose invariance.
The paper explores how magnetic systems' spectra can identify metrics and 1-forms.
In this article we propose a new geometrization of the radiative phase space of asymptotically flat space-times: we show that the geometry induced on null-infinity by the presence of gravitational waves can be understood to be a generalisation of the tractor calculus of conformal manifolds adapted to the case of degene…
Robust Bayes-Assisted Conformal Prediction improves prediction set sizes.
Robust Bayes-Assisted Conformal Prediction improves prediction set sizes.
Study of superintegrable systems linked to affine hypersurfaces.
Deep learning reconstructs pressure fields and classifies leakage rates in CCS storage sites.
COLEP improves robustness of conformal prediction via probabilistic circuits.
CPP solves chance constrained optimization problems with a framework that combines samples and quantile lemma.
Improved neural speaker embeddings enhance ASR performance.
Generalizes Fefferman's structure to CR three-manifolds with additional data.
To a compact hyperbolic Riemann surface, we associate a finitely summable spectral triple whose underlying topological space is the limit set of a corresponding Schottky group, and whose ``Riemannian'' aspect (Hilbert space and Dirac operator) encode the boundary action through its Patterson-Sullivan measure. We prove …
In this paper, we investigate the prescribed scalar curvature problem on a non-compact Riemannian manifold , namely the existence of a conformal deformation of the metric realizing a given function as its scalar curvature. In particular, the work…
We discuss training techniques, objectives and metrics toward personalization of deep learning models. In machine learning, personalization addresses the goal of a trained model to target a particular individual by optimizing one or more performance metrics, while conforming to certain constraints. To personalize, we i…
It is known that all weakly conformal Hamiltonian stationary Lagrangian immersions of tori in the complex projective plane may be constructed by methods from integrable systems theory. This article describes the precise details of a construction which leads to a form of classification. The immersion is encoded as spect…
We study the dynamics of the vector field on an open surface given by the gradient of a Green's function. This dynamical approach enables us to show that this field induces an invariant decomposition of the surface as the union of a disk and a 1-skeleton that encodes the topology of the surface. We analyze the structur…
PPC detects anomalies in high-dimensional data efficiently.
We present a number of conditions which are necessary for an n-dimensional projective structure (M,[nabla]) to include the Levi-Civita connection nabla of some metric on M. We provide an algorithm, which effectively checks if a Levi-Civita connection is in the projective class and, in the positive, which finds this con…
Unsupervised mesh disentanglement separates identity and pose.
We consider the Laplacian associated with a general metric in the canonical conformal structure of the noncommutative two torus, and calculate a local expression for the term a_4 that appears in its corresponding small-time heat kernel expansion. The final formula involves one variable functions and lengthy two, three …
We develop a generalisation of disentanglement in VAEs---decomposition of the latent representation---characterising it as the fulfilment of two factors: a) the latent encodings of the data having an appropriate level of overlap, and b) the aggregate encoding of the data conforming to a desired structure, represented t…
We review aspects of twistor theory, its aims and achievements spanning thelast five decades. In the twistor approach, space--time is secondary with events being derived objects that correspond to compact holomorphic curves in a complex three--fold -- the twistor space. After giving an elementary construction of this s…
A machine learning model captures non-Newtonian fluid dynamics from molecular details.