Boundary rigidity proven for non-reversible Finsler metrics.
problem Recovering non-reversible Finsler metrics from boundary distance data.
method Sum of reversible Finsler norm and closed 1-form, boundary rigidity results.
result 1-form can be uniquely recovered from boundary distance data.
Characterizes isometries between non-reversible Finsler manifolds.
problem Understanding isometries in non-reversible Finsler manifolds.
method Generalization of Myers-Nakai Theorem for Riemannian manifolds, modification of function spaces to accommodate asymmetric structure.
result Functional characterization of isometries between non-reversible Finsler manifolds.
Study functional inequalities on non-reversible Finsler manifolds.
problem Functional inequalities on non-reversible Finsler manifolds.
method Application of Bochner inequality and Γ-calculus.
result Dimensional versions of Poincare--Lichnerowicz, logarithmic Sobolev, and Sobolev inequalities hold for non-reversible metrics.
Study of parabolas in Funk metric on unit disk.
problem Understanding parabolas in Funk metric on a disk.
method Analyzing four types of parabolas due to Funk metric's non-reversibility.
result Two known conics and two irreducible quartics found.
In the asymmetric setting, Hilbert's fourth problem asks to construct and study all (non-reversible) projective Finsler metrics: Finsler metrics defined on open, convex subsets of real projective n-space for which geodesics lie on projective lines. While asymmetric norms and Funk metrics provide many examples of esse…
We develop the basics of a theory of almost isometries for spaces endowed with a quasi-metric. The case of non-reversible Finsler (more specifically, Randers) metrics is of particular interest, and it is studied in more detail. The main motivation arises from General Relativity, and more specifically in spacetimes endo…
Study on how non-reversible diffusion processes affect homology on manifolds.
problem Understanding the asymptotic behavior of random homology in diffusion processes.
method Investigation of asymptotic properties of random homology associated with stochastic diffusion processes on compact Riemannian manifolds.
result For quadratic rate, manifold is a locally trivial fiber bundle over a flat torus with minimal fibers.
We show the existence of at least two geometrically distinct closed geodesics on an n-dimensional sphere with a bumpy and non-reversible Finsler metric for n>2.
For non-reversible Finsler metrics of positive flag curvature on spheres and projective spaces we present results about the number and the length of closed geodesics and about their stability properties.
Develops semigroup approach for Finsler geometry, proving isoperimetric inequality.
problem Proving isoperimetric inequality for Finsler manifolds.
method Semigroup approach, Bochner-Weitzenböck formula, gradient estimate, lower weighted Ricci curvature bound.
result Proves Bakry-Ledoux's Gaussian isoperimetric inequality for non-reversible metrics.
A new sampler speeds up Bayesian mixture models.
problem Sampling from Bayesian finite mixture models is slow and hard.
method Introduces a non-reversible sampling scheme for Bayesian finite mixture models.
result The new sampler outperforms classical samplers in many scenarios, especially during convergence.
We give a lower bound for the length of a non-trivial geodesic loop on a simply-connected and compact manifold of even dimension with a non-reversible Finsler metric of positive flag curvature. Harris and Paternain use this estimate in their recent paper [HP] to give a geometric characterization of dynamically convex F…
Two distinct geodesics on spheres with a bumpy metric were shown.
problem Existence of two distinct closed geodesics on spheres with a non-reversible and bumpy Finsler metric.
method Simplified proof using covering geodesics and minimal index growth.
result Contradiction for infinite index, leading to the existence of two distinct geodesics.
Adaptive algorithm improves convergence rate of Langevin dynamics.
problem Improving convergence rate of Langevin dynamics.
method Adaptive non-reversible stochastic gradient Langevin dynamics algorithm.
result Improved convergence rate of the algorithm.
Paper studies metric properties on geodesic spaces to characterize curvature negativity.
problem Characterizing curvature negativity in geodesic spaces.
method Introduces metric properties via metric projection and applies to Alexandrov and Busemann NPC spaces.
result Proves both properties characterize non-positivity of sectional curvature on Riemannian manifolds.
For odd-dimensional spheres, there's always a second short geodesic.
problem Finding the second shortest closed geodesic on odd-dimensional spheres.
method Analyzing non-reversible Finsler metrics on spheres of odd dimension.
result There is a second closed geodesic with Morse index ≤ 4(m+2)(m-1)+2.
NSGLD improves SGLD for non-convex optimization problems.
problem Optimizing non-convex objectives efficiently.
method Introducing non-reversible SGLD by adding an anti-symmetric matrix to the drift term of the Langevin diffusion.
result NSGLD converges faster to the same stationary distribution with non-asymptotic guarantees.
In this article, we show that a Finsler--Laplacian introduced previously can detect changes in the Finsler metric that the marked length spectrum cannot. We also construct examples of non-reversible Finsler metrics in negative curvature such that 4λ1>h2, where λ1 is the bottom of the L2-spectrum and h the…
New method improves convergence of gradient descent for non-convex, non-reversible Markov chains.
problem Improving convergence of gradient descent for non-convex, non-reversible Markov chains.
method Introducing a new technique that varies the mixing levels of the Markov chains to establish non-ergodic convergence under wider step sizes.
result Established non-ergodic convergence for non-convex problems and non-reversible finite-state Markov chains.
New non-reversible Langevin dynamics improve global optimization efficiency.
problem Optimizing non-convex functions efficiently.
method Underdamped and non-symmetric drift Langevin dynamics.
result Non-reversible variants can exit local minima faster and explore state space better.
Using the definition of a Finsler--Laplacian given by the first author, we show that two bi-Lipschitz Finsler metrics have a controlled spectrum. We deduce from that several generalizations of Riemannian results. In particular, we show that the spectrum on Finsler surfaces is controlled above by a constant depending on…
A method to generalize results from Riemannian Geometry to Finsler geometry is presented. We use the method to generalize several results that involve only metric conditions. Between them we show that the topology induced by the Finsler structure is equivalent to the manifold topology, we provide a new proof of the Hop…
We give the details of the proof of the equality between the critical groups, with respect the H^1 and C^1 topology, at a non-degenerate critical point of the energy functional of a non-reversible Finsler manifold (M,F), defined on the Hilbert manifold of the H^1 curves connecting two given points on M.
A new sampler improves the inference of causal structures from observational data.
problem Inferring causal relationships from observational data when DAGs are Markov equivalent.
method Developed a non-reversible Markov chain, Causal Zig-Zag sampler, targeting Markov Equivalence Classes of DAGs.
result The sampler improves mixing and offers efficient algorithms for DAG inference.
A Clifford-Wolf translation of a connected Finsler space is an isometry which moves each point the sam distance. A Finsler space (M,F) is called Clifford-Wolf homogeneous if for any two point x1,x2∈M there is a Clifford-Wolf translation ρ such that ρ(x1)=x2. In this paper, we study Clifford-Wolf transl…
In this paper we first study some global properties of the energy functional on a non-reversible Finsler manifold. In particular we present a fully detailed proof of the Palais--Smale condition under the completeness of the Finsler metric. Moreover we define a Finsler metric of Randers type, which we call Fermat metric…
The paper analyzes variance reduction in stochastic gradient Langevin dynamics.
problem Reducing the variance of stochastic gradient estimators in Langevin dynamics.
method Central limit theorem and Poisson equation analysis for variance characterization.
result Anti-symmetric perturbations can reduce the variance of non-reversible Langevin dynamics.
Study geodesics on spheres with constant curvature, showing integrability and invariant properties.
problem Characterizing geodesics on spheres with constant flag curvature.
method Analyzing non-reversible Finsler metrics on S2 with constant flag curvature 1. result Geodesic flow is conjugate to Katok's examples and length of shortest closed geodesic is invariant.
The book covers scalable MCMC methods for Bayesian learning.
problem Scalability issues in Bayesian learning with large datasets.
method Advanced MCMC algorithms, including stochastic gradient, non-reversible, and continuous time methods.
result Substantial advances in practical and theoretical Bayesian computation.
HDT improves MCMC on graphs with history-dependent sampling.
problem Efficient sampling from target distributions on general graphs with low computational overhead.
method History-driven target (HDT) framework that replaces the original target distribution with a history-dependent one.
result Near-zero variance performance and scalability to large graphs with memory-efficient implementation.
The paper estimates Betti numbers for graphs with specific curvatures, proving bounds and characterizing rigidity.
problem Estimating Betti numbers for graphs with non-negative curvatures.
method Establishing Betti number estimates for graphs with non-negative Ollivier and Bakry-Émery curvatures.
result Upper bounds on the first Betti number for graphs with non-negative curvatures, with characterizations of rigidity.
Estimates mixing time of non-reversible Markov chains from a single trajectory.
problem Estimating mixing time of non-reversible Markov chains from a single trajectory.
method Estimates pseudo-spectral gap instead of spectral gap, achieving polynomial dependence on minimal stationary probability and pseudo-spectral gap.
result Achieves polynomial dependence on minimal stationary probability and pseudo-spectral gap, overcoming the loss of symmetry.
Estimates Markov chain mixing time from a single trajectory.
problem Estimating mixing time of Markov chains from a single trajectory.
method Contraction with respect to total variation, inspired by Wolfer's contraction coefficient.
result Improved confidence intervals and instance-dependent rates for estimating Markov chains.
Klartag recently gave a beautiful alternative proof of the isoperimetric inequalities of Levy-Gromov, Bakry-Ledoux, Bayle and E. Milman on weighted Riemannian manifolds. Klartag's approach is based on a generalization of the localization method (so-called needle decompositions) in convex geometry, inspired also by opti…
A new model predicts wildfire spread with wind and slope effects.
problem Predicting wildfire spread with wind and slope effects.
method Geometric model based on Lorentz-Finsler framework, considering wind and slope.
result Infinitesimal wavefronts are no longer restricted to be elliptical, allowing for more accurate predictions.
New orbits found in Lagrangian systems on surfaces.
problem Finding action minimizing periodic orbits in Tonelli Lagrangian systems.
method Analyzing minimal boundaries and using graph theorems.
result Existence of action minimizing simple periodic orbits.
Blang simplifies Bayesian analysis for non-standard data types.
problem Bayesian inference for non-standard data structures.
method Bayesian declarative language, distribution continua, sequential Monte Carlo, non-reversible MCMC.
result Bayesian analysis on arbitrary data types is feasible and efficient.
New PDMP samplers tackle variable selection in models.
problem Jointly explore model space and parameter space.
method Develop reversible jump PDMP samplers.
result New samplers mix better and are more efficient.
This work accelerates constrained sampling using large deviation principles.
problem Sampling constrained probability distributions efficiently.
method Large deviation principles applied to skew-reflected non-reversible Langevin dynamics.
result The skew-symmetric matrix accelerates convergence and reduces asymptotic variance.
Binary BPS improves sampling for easy mixtures.
problem Sampling from binary distributions efficiently.
method Generalized Bouncy Particle Sampler for binary variables.
result Binary BPS outperforms binary HMC for easy mixtures.
We investigate the question of the existence of a Lagrangian concordance between two Legendrian knots in R3. In particular, we give obstructions to a concordance from an arbitrary knot to the standard Legendrian unknot, in terms of normal rulings. We also place strong restrictions on knots that have concord…
The paper proves inequalities for Steklov eigenvalues on finite graphs.
problem Eigenvalues of Laplacians for reversible Markov chains and Steklov eigenvalues.
method Generalized Cheeger inequalities, convergence results, and resolvent convergence.
result Sharp estimate for the first non-trivial Steklov eigenvalue.
Study on convergence of SDEs using entropy methods.
problem Analyzing convergence of stochastic differential equations.
method Applied Lyapunov method to Fokker-Planck equation with weighted relative Fisher information.
result Exponential convergence of probability density function to invariant distribution in L1 distance. New methods improve efficiency of sampling algorithms for complex systems.
problem Efficiently sampling from complex, high-dimensional probability distributions.
method Randomized Runge-Kutta-Nyström methods tailored for Hamiltonian flows.
result Quantitative 5/2-order L2-accuracy in approximating Hamiltonian flows. Study homology products on loop spaces with orientation reversal.
problem Computing homology products on loop spaces with orientation reversal.
method Defined transfer product on loop space quotients using transfer maps and Chas-Sullivan loop product.
result Computed homology of loop spaces with orientation reversal and defined product.
Study of intersections in Hamiltonian orbits on cotangent bundles.
problem Understanding intersections of projected Hamiltonian orbits in cotangent bundles.
method Generic submersive level set analysis, multi-jet transversality theorem.
result Projected Hamiltonian orbits have discrete intersections, which can be perturbed away under certain conditions.
A new stochastic version of BPS improves sampling from big datasets.
problem Efficiently sampling Bayesian posteriors in large datasets.
method Stochastic Bouncy Particle Sampler using thinning method of Poisson process.
result The algorithm outperforms other samplers in efficiency and mixing.
We introduce a novel class of labeled directed acyclic graph (LDAG) models for finite sets of discrete variables. LDAGs generalize earlier proposals for allowing local structures in the conditional probability distribution of a node, such that unrestricted label sets determine which edges can be deleted from the underl…