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arXiv research

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.

168,694 papers · 148 categories

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336698131 · Jun 202019922001200920172026
48 results for obstacle interaction

Study on elastic curves pinned at the boundary, focusing on minimizers and their interaction with obstacles.

problem Minimizing elastic bending energy for open planar curves with obstacles.
method Investigation of global minimizers and explicit solutions for different values of the penalization parameter.
result Explicit threshold for λλ above which minimizers touch the obstacle, regardless of obstacle shape.

Study finds a limiting distribution for free path lengths on flat surfaces with circular obstacles.

problem Understanding free path lengths on flat surfaces with circular obstacles.
method Proved the existence of a limiting distribution using radius of obstacles as a parameter.
result Relates the limiting distribution to heights of zippered rectangle decompositions.

The paper deals with some problems related to recovering information about an obstacle in an Euclidean space from certain measurements of lengths of generalized geodesics in the exterior of the obstacle. The main result is that if two obstacles satisfy some generic regularity conditions and have (almost) the same trave…

2014-04-16abs ↗pdf ↗

New approach for obstacle avoidance in robotics using learned representations.

problem Challenges in sensor-based motion planning for new and dynamic environments.
method Proposes a new obstacle representation using PointNet architecture trained jointly with policies for obstacle avoidance.
result Significant improvements in accuracy and efficiency compared to state of the art.

The paper finds local minimizers for obstacle avoidance on curved spaces.

problem Finding optimal paths on curved spaces avoiding obstacles.
method Minimizing an action functional with bi-Jacobi fields and biconjugate points.
result Local minimizers are classified into two categories with local uniqueness results.

PHASE dataset simulates complex social interactions in physical environments.

problem Lack of datasets for evaluating physically grounded perception of complex social interactions.
method Created PHASE dataset of 2D animations with procedural generation and physics engine.
result SIMPLE model outperforms neural networks in recognizing complex social interactions.

The paper simplifies conditions for optimal paths on manifolds avoiding obstacles.

problem Finding optimal paths on manifolds avoiding obstacles.
method Study of sufficient conditions for optimality on Riemannian manifolds and Lie groups.
result New conditions for optimality are provided in terms of matrix invertibility.

Study anisotropic obstacle problem for minimal surfaces using Cahn-Hoffman transform.

problem Anisotropic obstacle problem for minimal surfaces.
method Cahn-Hoffman transform to convert to isotropic problem with generalized Robin boundary condition.
result Optimal regularity of the solution and C1,1C^{1,1} regularity of the free boundary.

A new method predicts higher-order interactions in evolving graphs using simplicial complexes.

problem Predicting higher-order interactions in dynamic graphs with theoretical guarantees.
method Capturing higher-order interactions as simplices, modeling neighborhoods with face-vectors, and developing a nonparametric kernel estimator.
result Our method outperforms existing higher-order prediction methods and is theoretically consistent.

We consider the broken ray transform on Riemann surfaces in the presence of an obstacle, following earlier work of Mukhometov. If the surface has nonpositive curvature and the obstacle is strictly convex, we show that a function is determined by its integrals over broken geodesic rays that reflect on the boundary of th…

2014-03-20abs ↗pdf ↗

Anisotropic obstacle problems and Stefan problem studied with evolving surfaces.

problem Anisotropic parabolic obstacle problems and Stefan problem.
method Cahn-Hoffman transform and anisotropic mean curvature flow.
result Optimal regularity of the solution and C1,αC^{1,α}-regularity of the evolving free boundary.

We consider an obstacle problem for elastic curves with fixed ends. We attempt to extend the graph approach provided in [8]. More precisely, we investigate nonexistence of graph solutions for special obstacles and extend the class of admissible curves in a way that an existence result can be obtained by a penalization …

2018-12-07abs ↗pdf ↗

In this paper, we analyze a real-valued reflected backward stochastic differential equation (RBSDE) with an unbounded obstacle and an unbounded terminal condition when its generator ff has quadratic growth in the zz-variable. In particular, we obtain existence, comparison, and stability results, and consider the opti…

2010-05-19abs ↗pdf ↗

This paper presents preliminary work on learning the search heuristic for the optimal motion planning for automated driving in urban traffic. Previous work considered search-based optimal motion planning framework (SBOMP) that utilized numerical or model-based heuristics that did not consider dynamic obstacles. Optimal…

2018-05-25abs ↗pdf ↗

Billiard trajectories (broken generalised geodesics) are considered in the exterior of an obstacle KK with smooth boundary on an arbitrary Riemannian manifold. We prove a generalisation of the well-known Santalo's formula. As a consequence, it is established that if the set of trapped points has positive measure, then…

2016-01-15abs ↗pdf ↗

A framework for navigating environments with spatially correlated obstacles and uncertain blockage status.

problem Navigation in environments with spatially correlated obstacles of uncertain blockage status.
method Modeling spatial correlation with Gaussian Random Field, developing Bayesian belief updates, proposing a two-stage learning framework with offline and online phases.
result Consistent performance gains over baselines in environments with adversarial interruptions or clustered natural hazards.

GP-ND avoids obstacles in trajectory planning using Gaussian Process regression.

problem Avoiding obstacles in trajectory planning for real-world systems.
method GP-ND models negative data pairs using Gaussian distributions and maximizes their KL divergence from the GP to avoid them.
result GP-ND outperforms traditional GP learning in obstacle-aware trajectory planning.

This work adopts the very successful distributional perspective on reinforcement learning and adapts it to the continuous control setting. We combine this within a distributed framework for off-policy learning in order to develop what we call the Distributed Distributional Deep Deterministic Policy Gradient algorithm, …

2018-04-23abs ↗pdf ↗

The Heston stochastic volatility process is a degenerate diffusion process where the degeneracy in the diffusion coefficient is proportional to the square root of the distance to the boundary of the half-plane. The generator of this process with killing, called the elliptic Heston operator, is a second-order, degenerat…

2012-06-05abs ↗pdf ↗

We prove that if two non-trapping obstacles in Rn\mathbb{R}^n satisfy some rather weak non-degeneracy conditions and the scattering rays in their exteriors have (almost) the same travelling times or (almost) the same scattering length spectrum, then they coincide.

2017-09-06abs ↗pdf ↗

Consider an assistive system that guides visually impaired users through speech and haptic feedback to their destination. Existing robotic and ubiquitous navigation technologies (e.g., portable, ground, or wearable systems) often operate in a generic, user-agnostic manner. However, to minimize confusion and navigation …

2018-04-11abs ↗pdf ↗

Study on semiconcavity of solutions to gradient obstacle problems on compact manifolds.

problem Gradient obstacle problems on compact Riemannian manifolds.
method Uniform semiconcavity estimates and fine convergence results for solutions and free boundaries.
result The elastic and λλ-elastic sets of solutions converge to the cut locus and λλ-cut locus of the manifold.

One obstacle to applying reinforcement learning algorithms to real-world problems is the lack of suitable reward functions. Designing such reward functions is difficult in part because the user only has an implicit understanding of the task objective. This gives rise to the agent alignment problem: how do we create age…

2018-11-19abs ↗pdf ↗

Coordinated defensive escorts can aid a navigating payload by positioning themselves in order to maintain the safety of the payload from obstacles. In this paper, we present a novel, end-to-end solution for coordinating an escort team for protecting high-value payloads. Our solution employs deep reinforcement learning …

2019-10-09abs ↗pdf ↗

Rigidity of travel times for convex obstacles in Riemannian manifolds is proven.

problem Rigidity of travel times for strictly convex obstacles in Riemannian manifolds.
method Analysis of billiard trajectories and comparison of travel times.
result If travel times are equal, then obstacles are identical in dimensions greater than or equal to 3.

By introducing a shape manifold as a solution set to solve inverse obstacle scattering problems we allow the reconstruction of general, not necessarily star-shaped curves. The bending energy is used as a stabilizing term in Tikhonov regularization to gain independence of the parametrization. Moreover, we discuss how se…

2019-03-12abs ↗pdf ↗

The paper studies the properties of maps with free boundaries, focusing on the obstacle case.

problem Properties of the projected image and its regularity in maps with free boundaries.
method Dividing the map into distance and projected image parts; applying classical obstacle problem methods and proving higher regularity for the projected image.
result The projected image is at most of class C2,1C^{2,1} and globally of class W3,BMOW^{3,BMO}, locally of C2,1C^{2,1} around the regular part of the free boundary.