New inequalities for Steklov eigenvalues traced and inverted.
problem Steklov eigenvalues and their traces.
method Obtained new inequalities for Steklov eigenvalues.
result New inequalities for trace and inverse trace of Steklov eigenvalues.
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48 results for “inverse trace”
Paper improves estimates for Steklov eigenvalues.
problem Estimating Steklov eigenvalues and their inverses.
method Generalizes previous results using new estimates.
result New estimates for trace and inverse trace of Steklov eigenvalues.
Develops trace class operators and inverse Laplacian theory for infinite dimensions.
problem Understanding trace class operators and inverse Laplacian on infinite dimensional spaces.
method Presentation of trace class operators and construction of inverse Laplacian on closed manifolds.
result Original trace computations involving the inverse Laplacian on the torus.
Deep learning model improves seismic rock property estimation.
problem Estimating reservoir rock properties from seismic reflection data.
method Proposes a deep learning-based seismic inversion workflow that models seismic traces spatiotemporally.
result Achieves best performance on SEAM dataset with coefficient of 79.77\%
Paper proves stability for recovering connections from holonomy traces.
problem Recovering a connection from holonomy traces on Riemannian manifolds.
method Combination of microlocal analysis and non-Abelian approximate Livsic Theorem.
result Hölder type stability estimates for holonomy inverse problem.
The wave trace of certain convex domains can be smooth near some points in the length spectrum.
problem Understanding the relationship between the wave trace and the length spectrum of convex domains.
method Constructing silent periodic billiard orbits with the same length but different Maslov indices, using a microlocal parametrix for wave invariants.
result The wave trace can be smooth near some points in the length spectrum, showing potential limitations for inverse spectral problems.
Seismic inversion improved using semi-supervised sequence modeling.
problem Lack of geophysical constraints in machine learning seismic inversion.
method Semi-supervised sequence modeling with recurrent neural networks.
result Achieved 98% correlation between estimated and target elastic impedance.
Improves inverse uncertainty quantification for time-dependent data using PCA and deep neural networks.
problem Efficiently quantify model input uncertainties from time-dependent experimental data.
method Functional PCA for dimensionality reduction, deep neural networks for surrogate modeling, Bayesian neural networks for uncertainty estimation.
result The proposed method reduces the computational cost and improves the agreement with experimental data.
New rigidity result for Steklov eigenvalues on manifolds.
problem Steklov eigenvalues on manifolds.
method Decomposition theorem for flat and totally geodesic Riemannian submersions.
result Equality of trace estimate holds if and only if the manifold is a direct product of a round ball and a closed manifold.
Automates hair color digitization using imaging and deep learning.
problem Challenges in capturing and rendering realistic hair colors.
method Combines imaging, path-tracing, and self-supervised machine learning.
result Accurately captures and renders hair color with synthetic images.
Study shows trace and mass of subcritical GJMS operators on manifolds.
problem Characterize the trace and mass of subcritical GJMS operators.
method Analyzes zeta-regularized trace of inverse GJMS operator, uses positive mass theorems.
result Supremum of trace is greater than or equal to standard sphere, attains constant mass under certain conditions.
We study the inverse spectral problem for weighted projective spaces using wave-trace methods. We show that in many cases one can "hear" the weights of a weighted projective space.
New principle for supersymmetric localization on Lie groups.
problem Computing supertrace of non-supersymmetric observables.
method Invariant supersymmetric deformations and fermionic zero modes.
result Path integral localizes to periodic orbits.
In Alain Connes noncommutative geometry, the question of the existence of a non-trivial integral can be described in terms of the singular traceability of the compact operator |D|^(-d), D being the Dirac operator, namely of the existence of a finite non-trivial singular trace on the ideal generated by |D|^(-d). A condi…
In this paper we study properties of the Markov trace and the specialized trace on the Yokonuma-Hecke algebras, such as behaviour under inversion of a word, connected sums and mirror imaging. We then define invariants for framed, classical and singular links through the trace ${\rm tr}_{d,…
The paper proves properties of robust diffeomorphisms and their invariant sets.
problem Investigating robust diffeomorphisms and their invariant sets.
method Demonstrates the robust inverse shadowing property on chain recurrent and transitive sets.
result Proves that invariant sets are hyperbolic under robust inverse shadowing.
Study magnetic potentials on Anosov manifolds using spectral data.
problem Recover magnetic potentials from spectral data on Anosov manifolds.
method Utilize principal wave trace invariants and magnetic Schrödinger operator.
result Spectral data uniquely determines magnetic and electric potentials on Anosov manifolds.
ACI uses Bayesian data assimilation to trace causes from effects in complex systems.
problem Capturing instantaneous, time-evolving causal relationships in complex, high-dimensional systems.
method Assimilative causal inference (ACI) leverages Bayesian data assimilation to trace causes backward from observed effects.
result ACI provides online tracking of causal roles that may reverse intermittently and reveals how far effects propagate.
Determinantal averaging corrects inversion bias in distributed Newton's method.
problem Inverting a sum of distributed matrices is biased; local averages are incorrect.
method Reweighting local estimates of the Newton's step proportionally to the determinant of the local Hessian estimate, then averaging them.
result Determinantal averaging provides the first known asymptotically consistent distributed Newton step.
p-adic framed braidsmath.GR
In this paper we define the -adic framed braid group , arising as the inverse limit of the modular framed braids and we give topological generators for . We also give geometric interpretations for the -adic framed braids. We then construct a -adic Yokonuma-Hec…
Matrix formulas for knot invariants derived from Tait graphs.
problem Computing knot invariants for alternating links.
method Squarefree matrix extraction from Tait graph vertices.
result Explicit formulas for for .
Researchers solve an inverse problem for a semilinear elliptic equation on complex manifolds.
problem Determining an unknown function in a semilinear elliptic equation on complex manifolds.
method Analyzing higher order linearizations and interactions of Gaussian quasimode solutions.
result An unknown smooth function can be uniquely determined from the Dirichlet-to-Neumann map.
GL-LowPopArt improves minimax-optimal estimation for trace regression.
problem Minimizing estimation error in generalized low-rank trace regression.
method Two-stage approach: nuclear norm regularization followed by matrix Catoni estimation.
result Achieves instance-wise optimal error bounds up to condition number.
This paper presents a unified geometric framework for the statistical analysis of a general ill-posed linear inverse model which includes as special cases noisy compressed sensing, sign vector recovery, trace regression, orthogonal matrix estimation, and noisy matrix completion. We propose computationally feasible conv…
We prove inverse spectral results for differential operators on manifolds and orbifolds invariant under a torus action. These inverse spectral results involve the asymptotic equivariant spectrum, which is the spectrum itself together with "very large" weights of the torus action on eigenspaces. More precisely, we show …
VTA combines verbal and latent reasoning for accurate stock time-series forecasts.
problem Challenges in combining textual analysis with time-series data for financial forecasting.
method Converts stock price data into textual annotations, optimizes reasoning trace using inverse MSE, conditions time-series model outputs on reasoning attributes.
result VTA achieves state-of-the-art forecasting accuracy and interpretable reasoning traces.
Multi-output Gaussian processes for inverse uncertainty quantification in neutron noise analysisstat.CO
The paper tackles inverse uncertainty quantification in neutron noise analysis.
problem Uncertainty in estimating material properties from noisy neutron correlation measurements.
method Surrogate models and inverse uncertainty quantification to account for measurement error and model bias.
result Improved prediction of neutron correlations and quantification of uncertainties.
The paper solves the Steklov spectral inverse problem for conformal metrics.
problem Recovering a metric from its Steklov spectrum in dimension n≥3.
method Combines wave trace formula techniques with geodesic X-ray transform.
result Steklov isospectral metrics must coincide under real-analyticity assumption.
New method reduces variance in Bayesian inverse problems.
problem High variance in Monte Carlo estimates for inverse problems.
method Conditional neural control variates based on Stein's identity.
result Substantial variance reduction across different inverse problems.
Paper estimates differences in multi-attribute Gaussian graphical models using non-convex penalties.
problem Estimating differences in multi-attribute Gaussian graphical models with similar structure.
method Penalized D-trace loss function with non-convex (log-sum and SCAD) penalties, proximal gradient descent methods.
result Theoretical analysis and numerical examples support consistency in support recovery and estimation.
Paper introduces STSL, a second-order Tweedie sampler for efficient posterior sampling in inverse problems.
problem Computational challenges in sampling from posterior distributions using latent diffusion models.
method Introduces STSL, a novel second-order Tweedie sampler with tractable reverse process.
result STSL achieves 4X and 8X reduction in neural function evaluations compared to state-of-the-art solvers.
Paper reveals how minimal surfaces' volumes can deduce their Riemannian structure.
problem Determining the Riemannian structure of minimal surfaces from their volumes.
method Analysis of Dirichlet-Neumann map and Carleman estimates.
result Volumes of minimal surfaces determine their Riemannian structure.
The Holonomy Inverse Problemmath.DS
The paper shows how to uniquely determine a connection up to gauge.
problem Determining a connection up to gauge from its holonomies.
method Using hyperbolic dynamical systems and transport operators.
result The primitive trace map is locally injective near generic points.
We define the "sum of squares of the wavelengths" of a Riemannian surface (M,g) to be the regularized trace of the inverse of the Laplacian. We normalize by scaling and adding a constant, to obtain a "mass", which is scale invariant and vanishes at the round sphere. This is an anlaog for closed surfaces of the ADM mass…
The paper calculates heat kernel and closed geodesic asymptotics for nilpotent coverings.
problem Heat kernel and closed geodesic asymptotics for nilpotent coverings.
method Finite-dimensional rational Floquet-Bloch theory, Pytlik functional, and spectral sums.
result Genuinely local, pointwise higher-order heat-kernel expansions.
The paper identifies all surfaces with two transversal circular arcs through each point.
problem Finding surfaces with two transversal circular arcs through each point.
method Uses a new factorization technique for quaternionic polynomials.
result Proves all such surfaces are images of subsets of specific sets under inversions.
New framework for designing cognitive experiments to infer latent cognitive mechanisms.
problem Designing optimal cognitive experiments for Bayesian inference of latent cognitive mechanisms.
method Formulated as a Bayesian Experimental Design (BED) problem, treating environments as design variables. Introduced an amortized Bayesian experimental design framework for efficient posterior inference and design evaluation.
result No single environment is uniformly optimal for all cognitive inference objectives, revealing trade-offs between expected information gain, posterior recoverability, and information efficiency.
SHMM models human mobility from GPS and text data, overcoming text sparsity.
problem Modeling human mobility from semantic trace data, especially addressing text sparsity.
method SHMM is a multi-modal spherical hidden Markov model that jointly models location, time, and text embeddings on a unit sphere using vMF distribution.
result SHMM outperforms state-of-the-art models in next location prediction and has lower training cost.
New framework calibrates decision robustness using inverse conformal risk control.
problem Inadequate robustness levels in decision-making due to ad hoc choices.
method Constructs valid estimators to trace miscoverage-regret Pareto frontier.
result Provides distribution-free, finite-sample guarantees on robustness levels.
Study of torus surgeries on knot traces, finding exotic surfaces and traces.
problem Understanding exotic surfaces and traces through torus surgeries.
method Realizing annulus twisting as torus surgery, using key technical insight.
result Exotic elliptic surfaces and traces discovered, improving known geography.
Classifies knot traces with specific trisection genus limits.
problem Classifying knot traces with specific trisection genus limits.
method Classifying knot traces with specific trisection genus limits.
result Infinitely many knots have traces with trisection genus 3 and 4, and arbitrarily large trisection genus.
Quantum heat tracesmath-ph
Quantum heat traces study new invariants from elliptic operators.
problem New invariants of elliptic operators on Riemannian manifolds.
method Relativistic and quantum heat traces, integral transforms, asymptotic expansion.
result Coefficients of asymptotic expansion determined by local and global invariants.
New MD algorithms using Tempesta logarithms for machine learning.
problem Optimization in machine learning with tailored hyperparameters.
method Developed Mirror Descent algorithms using Tempesta multi-parametric logarithms.
result Wide and flexible family of Mirror Descent and mirror-less updates.
Guillemin trace formula adapted for group actions.
problem Distributional trace for proper, cocompact group actions.
method Developing an equivariant version of the distributional trace.
result Equivariant Guillemin trace formula for group actions.
New inductive basis proves Markov trace existence and transverse traces determination.
problem Existence and characterization of traces on Birman-Murakami-Wenzl algebras.
method Inductive basis construction and proof of trace existence and determination.
result All transverse traces are determined by specific polynomials and link invariants.
Paper derives trace formula for magnetic Laplacian at zero energy.
problem Trace formula for magnetic Laplacian at zero energy.
method Generalizes Gutzwiller trace formula, focuses on zero energy level.
result Derives trace formula at zero energy level.
New methods derive a generalized Frenkel trace formula for Lie groups.
problem Deriving a generalized Frenkel trace formula for Lie groups.
method Applying supersymmetric localization to quantum mechanical and gauged sigma models.
result Presented two complementary approaches for the derivation of the trace formula.
Derives Selberg trace formula on Riemann surfaces and generalizes to other spaces.
problem Deriving and generalizing the Selberg trace formula.
method Supersymmetric localization principle and path integral derivation.
result Derives Selberg trace formula on arbitrary compact Riemann surfaces and generic compact locally symmetric spaces.