Study mass transport in low-diffusivity using Lagrangian coordinates.
problem Mass preserving transport of passive tracers in low-diffusivity limit.
method Lagrangian coordinates, time-averaged diffusion equation, weighted manifold structure.
result Leading order asymptotics extend to dominant nontrivial singular value in low-diffusivity limit.
New method converts and optimizes sampling schedules for generative models.
problem Optimizing sampling schedules for generative models like flows and diffusions.
method Unified framework for stochastic interpolants, including point mass schedules.
result Demonstrated efficient generation of images with fewer steps.
Method generates joint posterior samples of source and foreground mass distributions for gravitational lensing.
problem Challenging inference problem for high-resolution, high signal-to-noise ratio gravitational lensing.
method Combines diffusion-based generative modeling and recurrent inference machines.
result Can model realistic gravitational lensing simulations down to the noise level.
New framework analyzes regret in guided diffusion for optimizing structured inputs.
problem Understanding regret behavior in guided-diffusion black-box optimization for structured design problems.
method Developed a certificate-based expected simple-regret framework that avoids assumptions breaking down in modern diffusion BO pipelines.
result Explains how exponential and polynomial convergence can arise from mass lift in near-optimal designs.
Solves probabilistic Lambert problem connecting astrodynamics with optimal mass transport.
problem Determining spacecraft velocity for given positions with probabilistic constraints.
method Generalized optimal mass transport (OMT) and Schrödinger bridge (SBP) connections.
result Existence and uniqueness of solution for probabilistic Lambert problem.
SJDs unify masked, continuous, and hybrid diffusion models.
problem Unified modeling of diffusion processes.
method Continuous-time Markov processes with token embeddings and hazard rates.
result Unified model recovers masked, continuous, and hybrid diffusion as limits.
Link prediction improves future product export forecasts in the international trade network.
problem Predicting future evolution of complex systems like international trade networks.
method Applied link prediction algorithms based on heat and mass diffusion processes, improved with country fitness and product similarity metrics.
result Best results achieved with a new product similarity metric that considers causality.
Study shows how heat leaks from material sets in low diffusivity scenarios.
problem Understanding heat leakage from material sets in low diffusivity limits.
method Generalized leading-order asymptotics for time-dependent diffusion processes.
result Diffusive transport out of a material set is proportional to the surface area of the set boundary.
MF-PID uses interacting samples to efficiently transport probability mass.
problem Efficiently transporting probability mass in generative models.
method Introducing Mean-Field Path-Integral Diffusion (MF-PID) where samples become interacting agents.
result MF-PID achieves 19-24% reductions in control energy for demand-response control of energy systems.
Kernel-smoothed scores improve diffusion models by reducing memorization.
problem Diffusion models can memorize training data, leading to biased samples.
method Interpret empirical score as noisy version of true score, kernel-smoothed.
result Kernel-smoothing reduces variance and improves generalization.
Through the main example of the Ornstein-Uhlenbeck semigroup, the Bakry-Emery criterion is presented as a main tool to get functional inequalities as Poincaré or logarithmic Sobolev inequalities. Moreover an alternative method using the optimal mass transportation, is also given to obtain the logarithmic Sobolev inequa…
We solve a Schrödinger bridge with a quadratic state cost, finding a closed-form solution.
problem Optimizing diffusion processes between given distributions.
method Regularized Schrödinger bridge with a quadratic state cost.
result Closed-form solution for the Markov kernel of the regularized Schrödinger bridge.
The study uses heat flow to analyze properties of Laplace eigenfunctions on manifolds and domains.
problem Analyzing mass concentration and nodal domains of Laplace eigenfunctions.
method Heat diffusion technique to study eigenfunctions and their nodal sets.
result Discovers new insights into the decay and behavior of Laplace eigenfunctions.
New bidirectional model predicts magnetohydrodynamics fields and estimates uncertainty.
problem Predicting multiple fields in magnetohydrodynamics with uncertainty.
method Bidirectional autoregressive latent diffusion approach.
result Model can estimate uncertainty without ground truth using self-supervised consistency.
A new method models galaxies as points in space for better analysis.
problem Limitations of binning and voxelization in galaxy surveys.
method A diffusion-based generative model for galaxy point clouds.
result Demonstrated on dark matter haloes in Quijote simulations.
Optimizes diffusion processes for target distributions.
problem Efficiently generating target distributions from point masses.
method Stochastic interpolant framework with conditional expectation drift.
result Optimal diffusion coefficient minimizes path-space KL divergence.
New method recovers curvature from heat diffusion data.
problem Recovering Riemannian curvature from heat diffusion.
method Information-theoretic approach using relative entropy.
result Local curvature determined by heat diffusion.
The paper addresses boundary term learning in reflected diffusion models.
problem Boundary term learning in reflected diffusion models to ensure correct boundary behavior.
method Integration by parts and reflection masking techniques to enforce boundary conditions.
result The conormal trace of the diffusion-weighted normal component is crucial for boundary term learning.
New method learns diffusion transition density for Bayesian inference.
problem Bayesian inference on diffusions with inaccessible boundaries.
method Neural Galerkin framework to solve FP equation with Dirac mass.
result Approximates likelihood function for efficient posterior sampling.
Finite-time extinction and smoothing effects in fractional fast diffusion on manifolds.
problem Finite-time extinction and smoothing effects in fractional fast diffusion equations.
method Nonlinear semigroups techniques, weighted Lp spaces, fractional Green function. result Sharp extinction rates and pointwise lower bounds for solutions.
Geometrically, high-likelihood regions in DGMs are unlikely to generate OOD data.
problem The paradox of high-likelihood OOD detection in deep generative models.
method Local intrinsic dimension estimation to identify high-likelihood regions that do not generate OOD data.
result A method pairing likelihoods and LID estimates for reliable OOD detection.
New algorithm improves on existing methods for solving transport problems.
problem Finding a map to transport one distribution to another.
method Iterative Markovian Fitting (IMF) and Diffusion Schrödinger Bridge Matching (DSBM).
result DSBM significantly improves over previous SB numerics and recovers various transport methods.
This paper tackles denoising of complex measures using optimal transport and curvature analysis.
problem Denoising of complex, possibly non-log-concave measures.
method Score function and optimal transport theory to revert Langevin diffusion chains.
result The difficulty of denoising depends on the curvature complexity of the initial measure at specific SNR scales.
StAD predicts divergence of diffusion and flow models without Jacobian computation.
problem Computing likelihood from diffusion and flow models is computationally expensive.
method Introduces StAD, a distillation method to predict divergence using Langevin-Stein operator.
result StAD predicts divergence with competitive variance and speed compared to existing methods.
Global existence and smoothing effects for reaction-diffusion equations with blowup in infinite time.
problem Analyzing reaction-diffusion equations with power-type nonlinearity and slow diffusion.
method Functional analytic methods based on Sobolev and Poincaré inequalities.
result Solutions corresponding to large initial data blow up everywhere in infinite time on Cartan-Hadamard manifolds.
New algorithms improve MCMC efficiency for complex distributions.
problem High variance and low effective sample size in MCMC samplers.
method Antithetic Riemannian Manifold and Quantum-Inspired Hamiltonian Monte Carlo.
result Improved effective sample size and variance reduction.
MDNs offer a data-efficient alternative to diffusion and flow models for multimodal scientific learning.
problem Capturing multimodal conditional uncertainty in scientific inverse problems.
method Mixture Density Networks (MDNs) as explicit parametric density estimators.
result MDNs achieve superior generalization, interpretability, and sample efficiency in scientific tasks.
New method uses weighted SDEs to improve sampling from complex distributions.
problem Sampling from highly non-log-concave distributions.
method Introduces weighted stochastic differential equations to augment diffusion-based samplers.
result Demonstrates improved exploration of nonconvex or multimodal landscapes.
Paper analyzes tech adoption in financial networks, finding key leadership and diffusion dynamics.
problem Understanding technology adoption and network effects in financial systems.
method Developed a spatial-network framework with a master equation and Feynman-Kac representation.
result Found strong support for two-regime adoption dynamics and significant leadership in network central banks.
Schrödinger bridge solved with Weyl calculus for quadratic state cost.
problem Optimal control policy to steer joint state statistics.
method Weyl calculus in quantum mechanics for reaction-diffusion PDEs.
result Explicit Markov kernel for quadratic state cost found.
Modeling systemic risk with contagion effects in financial systems.
problem Capturing systemic risk and contagion effects in large financial systems.
method Dynamic mean field model derived from interacting diffusions with an absorbing boundary.
result The SPDE model exhibits periods of significant default clustering due to contagion.
Two masses on surfaces with boundary converge to ADM mass.
problem Evaluating quasi-local masses on surfaces with boundaries.
method Hawking mass and Huisken's isoperimetric mass on surfaces with boundary, convergence to ADM mass.
result Convergence of Hawking and Huisken's masses to ADM mass.
Total mass equals limits of quasi-local mass integrals.
problem Calculating total mass on complex manifolds.
method Evaluated total mass via Ricci tensor limits of quasi-local mass integrals.
result Limits of quasi-local mass integrals equal total mass.
The X-ADM mass is shown to be equivalent to the ADM mass, proving the X-positive mass theorem in all dimensions.
problem Proving the X-positive mass theorem for all dimensions.
method Conformal reduction argument.
result The X-ADM mass is equivalent to the ADM mass, proving the X-positive mass theorem in all dimensions.
The paper studies nonlinear mass concepts in 3-manifolds with nonnegative scalar curvature.
problem Nonlinear isocapacitary mass in 3-manifolds with nonnegative scalar curvature.
method Derives positive mass theorems and shows mass coincides with ADM mass under mild conditions.
result Nonlinear masses coincide with ADM mass and prove the Penrose inequality.
Diagonal Frog: High-order positivity-preserving FD schemes for anisotropic Fokker-Planck equations
problem Positivity-preserving discretizations for anisotropic Fokker-Planck equations
method Diagonal Frog discretization
result Second-order accuracy and mass conservation
Equivalence proven for isocapacitary mass notions.
problem Proving equivalence of isocapacitary mass notions.
method Proof of equivalence for G. Huisken's and J. L. Jauregui's isocapacitary mass.
result Equivalence of isocapacitary mass notions proven.
Formula for mass in higher-dimensional graphs proves mass theorems.
problem Proving mass theorems for higher-dimensional graphs.
method Explicit formula for Gauss-Bonnet-Chern mass, applied to asymptotically flat graphical manifolds.
result Proves positive mass theorem and Penrose inequality for graphs with flat normal bundle.
The paper defines a new mass quantity for 3-manifolds and proves a positive mass theorem.
problem Proving the positive mass theorem for a new geometric quantity.
method Defining X-ADM mass and using a monotonicity formula. result Established a relative positive mass theorem for asymptotically flat 3-manifolds.
Introduce new boundary mass for asymptotically flat half-manifolds
problem Define boundary mass for asymptotically flat half-manifolds
method Introduce new boundary mass
result Define boundary mass for asymptotically flat half-manifolds
The paper establishes geometric inequalities for quasi-local masses.
problem Lower bounds for quasi-local masses in terms of charge, angular momentum, and horizon area.
method Hamiltonian approach to three quasi-local masses: Brown-York, Liu-Yau, and Wang-Yau.
result Geometric inequalities motivated by ADM mass, interpreted as localized versions.
Study on Hawking and Bartnik masses for specific surfaces.
problem Analyzing the positivity and bounds of Hawking and Bartnik masses for constant mean curvature surfaces.
method Intrinsic conditions and estimates for the masses of constant mean curvature surfaces.
result Positivity and estimates of Hawking and Bartnik masses for surfaces with nonnegative scalar curvature.
Local mass at null infinity confirmed for Vaidya spacetime.
problem Positivity of quasi-local mass at null infinity.
method Solved optimal embedding equation and evaluated quasi-local mass.
result Quasi-local mass confirmed locally for Vaidya spacetime.
Researchers calculate quasi-local mass on unit spheres at infinity.
problem Computing quasi-local mass on unit spheres at spatial infinity.
method Developed new techniques to evaluate quasi-local mass.
result Leading order term of quasi-local mass recovers stress-energy tensor for vacuum spacetime.
Defines a new mass for flat manifolds equivalent to existing mass.
problem Defining a new mass for asymptotically flat manifolds.
method Uses Chern's magic form and Gauss-Bonnet-Chern curvature.
result Equivalence of new mass to existing mass.
Study bounds outer surfaces in small mass geometrostatic manifolds.
problem Bounding outer surfaces in geometrostatic manifolds with small ADM mass.
method Proving Intrinsic Flat Stability of the Positive Mass Theorem.
result Stability of the Positive Mass Theorem in geometrostatic manifolds with small ADM mass.
We prove directly without using a density theorem that (i) the ADM mass defined in the usual way on an asymptotically flat manifold is equal to the mass defined intrinsically using Ricci tensor; (ii) the Hamiltonian formulation of center of mass and the center of mass defined intrinsically using Ricci tensor are the sa…
Continuous metrics on R^3 with specific properties have non-negative harmonic mass.
problem Proving non-negativity of mass for continuous metrics.
method Defining harmonic mass and using properties of approximating smooth metrics.
result The harmonic mass of continuous metrics is non-negative.