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.
Universal model for soft tissue mechanics under shock waves.
Continuum mechanics theory describes skin's complex anisotropic behavior.
Data-driven approach learns effective equations for phase field interfaces.
We explore a computational model of an incompressible fluid with a multi-phase field in three-dimensional Euclidean space. By investigating an incompressible fluid with a two-phase field geometrically, we reformulate the expression of the surface tension for the two-phase field found by Lafaurie, Nardone, Scardovelli, …
We study the phase field method for the volume preserving mean curvature flow. Given an initial hypersurface we proved the existence of the weak solution for the volume preserving mean curvature flow via the reaction diffusion equation with a nonlocal term. We also show the monotonicity formula and the density up…
Machine learning predicts failure in brittle materials with high accuracy.
New proof confirms De Giorgi's conjecture about phase-field approximation of Willmore functional.
The homotopy theory of topological defects in ordered media fails to completely characterize systems with broken translational symmetry. We argue that the problem can be understood in terms of the lack of rotational Goldstone modes in such systems and provide an alternate approach that correctly accounts for the intera…
Optimizes structure topology for ductile and brittle fracture resistance.
Generates tubular and membranous shapes using curvature functionals.
We prove nonexistence of nonconstant local minimizers for a class of functionals, which typically appears in the scalar two-phase field model, over a smooth N-dimensional Riemannian manifold without boundary with non-negative Ricci curvature. Conversely for a class of surfaces possessing a simple closed geodesic along …
We consider the sharp interface limit of the Allen-Cahn equation with Dirichlet or dynamic boundary conditions and give a varifold characterization of its limit which is formally a mean curvature flow with Dirichlet or dynamic boundary conditions. In order to show the existence of the limit, we apply the phase field me…
In order to study a one-dimensional analogue of the spontaneous curvature model for two-component lipid bilayer membranes we consider planar curves that are made of a material with two phases. Each phase induces a preferred curvature to the curve, and these curvatures as well as phase boundaries may lead to the develop…
We present a new physics informed neural network (PINN) algorithm for solving brittle fracture problems. While most of the PINN algorithms available in the literature minimize the residual of the governing partial differential equation, the proposed approach takes a different path by minimizing the variational energy o…
Common models for two-phase lipid bilayer membranes are based on an energy that consists of an elastic term for each lipid phase and a line energy at interfaces. Although such an energy controls only the length of interfaces, the membrane surface is usually assumed to be at least across phase boundaries. We consi…
Study proposes a nonlocal approximation of the Willmore functional using fractional Allen-Cahn energies.
Study quantizes energy distribution in inhomogeneous phase transitions.
Variational approximations for curve flows on Riemannian manifolds.
The paper studies momentum-based minimization for Ginzburg-Landau on Euclidean spaces and graphs.
In this paper we study dynamic pricing mechanisms of financial derivatives. A typical model of such pricing mechanism is the so-called g--expectation defined by solutions of a backward stochastic differential equation with g as its generating function. Black-Scholes pricing model is a special linear case of this pricin…
A solution for the Weinstein's Problem in the general framework of generalized Lie algebroids is the target of this paper. We present the mechanical systems called by use, mechanical (?; ?)-systems, Lagrange mechanical (?; ?)-systems or Finsler mechanical (?; ?)-systems and we develop their geometries. We obtain the ca…
New mechanics on non-associative octonions discovered.
A new description, different by the classical theory of Hamiltonian Mechanics, in the general framework of generalized Lie algebroids is presented. In the particular case of Lie algebroids, new and important results are obtained. We present the \emph{dual mechanical systems} called by use, \emph{dual mechanical}$(ρ,η) …
This paper assesses Gaussian and Exponential mechanisms for certifying adversarial robustness.
We propose a new input perturbation mechanism for publishing a covariance matrix to achieve -differential privacy. Our mechanism uses a Wishart distribution to generate matrix noise. In particular, We apply this mechanism to principal component analysis. Our mechanism is able to keep the positive semi-definitene…
New mechanisms improve differential privacy for scalar queries.
We design two mechanisms for the recommender system to collect user ratings. One is modified Laplace mechanism, and the other is randomized response mechanism. We prove that they are both differentially private and preserve the data utility.
Quantum mechanics models for financial Black-Scholes model.
Differential privacy mechanism design has traditionally been tailored for a scalar-valued query function. Although many mechanisms such as the Laplace and Gaussian mechanisms can be extended to a matrix-valued query function by adding i.i.d. noise to each element of the matrix, this method is often suboptimal as it for…
Expands differential privacy mechanisms to include the Generalized Gaussian mechanism for improved private machine learning.
Optimal DP mechanisms for vector queries are found to be staircase distributions.
New approach identifies latent properties from mechanisms, not just data.
New RL approach learns dynamic VCG mechanisms in unknown MDP environments.
Paper connects dynamics of mechanical systems to Reeb dynamics.
Exact discrete mechanics for nonholonomic systems defined.
A new Gaussian mechanism for differential privacy in the shuffle model is introduced.
The key to a Transformer model is the self-attention mechanism, which allows the model to analyze an entire sequence in a computationally efficient manner. Recent work has suggested the possibility that general attention mechanisms used by RNNs could be replaced by active-memory mechanisms. In this work, we evaluate wh…
We study the problem of what causes prices to change. We define the mechanical impact of a trading order as the change in future prices in the absence of any future changes in decision making, and its it informational impact as the remainder of the total impact once mechanical impact is removed. We introduce a method o…
New mechanism for pure differential privacy on functional summaries using Laplace-like process.
Unified framework for subsampling mechanisms with tighter privacy guarantees.
New geometric mechanism solves four envelope problems.
This text explains how fiber bundle structure is fundamental for classical physics.
The paper improves privacy accounting for discrete-valued mechanisms and the subsampled Gaussian mechanism.
This paper examines allocation mechanisms in markets with transfer costs, showing how these costs affect economic efficiency.
The Gaussian mechanism is an essential building block used in multitude of differentially private data analysis algorithms. In this paper we revisit the Gaussian mechanism and show that the original analysis has several important limitations. Our analysis reveals that the variance formula for the original mechanism is …
Paper introduces a new deep-learning method for quantum mechanics.
Associating stock mechanics to real economy, in terms of volume, number of transactions, and cost, i.e. money flow for shares, we obtained the fundamental laws of stock mechanics.
CICME estimates common and domain-specific causal mechanisms from multi-sensor data.