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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.

168,657 papers · 148 categories

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82164245327 · Jun 202019922001200920172026
48 results for 3D examples

3D models vulnerable to adversarial attacks, new method improves success rate and naturalness.

problem Vulnerability of 3D deep learning models to adversarial examples in the physical world.
method ε-isometric (εε-ISO) attack considering geometric properties and invariance to physical transformations.
result Significantly improved attack success rate and naturalness of 3D adversarial examples.

The study connects knot complements to 3d theories via half-index calculations.

problem Understanding the relationship between knot complements and 3d theories.
method Using half-index calculations and inverted Habiro series, the study realizes knot complements as homological blocks.
result The colored Jones polynomial is derived from choosing specific poles in the half-index integral expression.

Study of IR phases in 3D class R theories linked to non-hyperbolic 3-manifolds.

problem Understanding IR phases of 3D class R theories associated with non-hyperbolic 3-manifolds.
method Analysis of IR phenomena through `exceptional' Dehn fillings and gauging of flavor symmetries.
result 3D class R theories associated with certain atoroidal non-hyperbolic 3-manifolds exhibit supersymmetry enhancement at low energy.

One of the challenges of using machine learning techniques with medical data is the frequent dearth of source image data on which to train. A representative example is automated lung cancer diagnosis, where nodule images need to be classified as suspicious or benign. In this work we propose an automatic synthetic lung …

2018-11-19abs ↗pdf ↗

The paper proposes methods for volumetric parameterization of 3D solid manifolds.

problem Complex structure of solid manifolds makes conventional approaches ineffective.
method Incorporates models to preserve geometric structure, achieve density equalization, and balance distortions.
result Various 3D manifold parameterizations with different properties can be achieved.

One of the main challenges in 3d-3d correspondence is that no existent approach offers a complete description of 3d N=2N=2 SCFT T[M3]T[M_3] --- or, rather, a "collection of SCFTs" as we refer to it in the paper --- for all types of 3-manifolds that include, for example, a 3-torus, Brieskorn spheres, and hyperbolic surgerie…

2019-11-19abs ↗pdf ↗

Proves Steiner and tube formulae for 3D contact sub-Riemannian surfaces.

problem Calculating surface properties in complex geometric structures.
method Develops a local Steiner formula for regular surfaces in 3D contact sub-Riemannian manifolds.
result Establishes a formula for surface expansion in arbitrary regions of contact sub-Riemannian manifolds.

In neural networks, it is often desirable to work with various representations of the same space. For example, 3D rotations can be represented with quaternions or Euler angles. In this paper, we advance a definition of a continuous representation, which can be helpful for training deep neural networks. We relate this t…

2018-12-17abs ↗pdf ↗

We present algorithms to compute the topology of 2D and 3D hyperelliptic curves. The algorithms are based on the fact that 2D and 3D hyperelliptic curves can be seen as the image of a planar curve (the Weierstrass form of the curve), whose topology is easy to compute, under a birational mapping of the plane or the spac…

2018-12-30abs ↗pdf ↗

Discover gaps in q-series exponents for 3d N=2 theories.

problem Understanding statistical properties of BPS q-series for 3d N=2 theories.
method Used principal component analysis with machine learning to calculate and analyze feature saliencies.
result Gaps in q-series exponents are statistically more significant at the beginning compared to higher powers.

The success of various applications including robotics, digital content creation, and visualization demand a structured and abstract representation of the 3D world from limited sensor data. Inspired by the nature of human perception of 3D shapes as a collection of simple parts, we explore such an abstract shape represe…

2017-08-04abs ↗pdf ↗

We study singularities of algebraic curves associated with 3d N=2 theories that have at least one global flavor symmetry. Of particular interest is a class of theories T_K labeled by knots, whose partition functions package Poincare polynomials of the S^r-colored HOMFLY homologies. We derive the defining equation, call…

2012-09-06abs ↗pdf ↗

Improved 3D MRI classification using contrastive learning with continuous proxy metadata.

problem Insufficient labelled data for 3D medical image classification.
method Proposed a new loss function (y-Aware InfoNCE) to leverage continuous proxy metadata in contrastive learning.
result 3D CNN model pre-trained on 10^4 multi-site healthy brain MRI scans outperforms fully-supervised methods.

We study knots in 3d Chern-Simons theory with complex gauge group SL(N,C)SL(N,\mathbb{C}), in the context of its relation with 3d N=2\mathcal{N}=2 theory (the so-called 3d-3d correspondence). The defect has either co-dimension 2 or co-dimension 4 inside the 6d (2,0)(2,0) theory, which is compactified on a 3-manifold M^\hat{M}. …

2015-10-13abs ↗pdf ↗

Simplified 3D Dijkgraaf-Witten theory with defects explained geometrically.

problem Constructing 3D Dijkgraaf-Witten theory with defects.
method Symmetric monoidal functor from defect cobordism category to vector spaces, using geometric and homotopy theoretic methods.
result Explicit construction of 3D untwisted Dijkgraaf-Witten theory with defects.

Study biharmonic conformal immersions into a 3D flat space, finding new examples and classifications.

problem Characterize and classify biharmonic conformal immersions into a conformally flat 3-space.
method Characterization of totally umbilical surfaces, method to produce biharmonic immersions, classification of maps, construction of examples.
result Construct many examples of biharmonic conformal immersions, including proper immersions and isometric ones.

Study of 3d-3d correspondence involving qq-Weyl algebra and 3d-index.

problem Understanding the action of a qq-Weyl algebra on the 3d-index of knots.
method Investigation of the qq-Weyl algebra's module action on the 3d-index, conjecturing structural properties.
result Bilinear factorization, pair of linear qq-difference equations, and rational function matrix for the 3d-index determination.

Using the locally compact abelian group $\BT \times \BZ$, we assign a meromorphic function to each ideal triangulation of a 3-manifold with torus boundary components. The function is invariant under all 2--3 Pachner moves, and thus is a topological invariant of the underlying manifold. If the ideal triangulation has a …

2017-06-25abs ↗pdf ↗

Autonomous driving requires 3D perception of vehicles and other objects in the in environment. Much of the current methods support 2D vehicle detection. This paper proposes a flexible pipeline to adopt any 2D detection network and fuse it with a 3D point cloud to generate 3D information with minimum changes of the 2D d…

2018-02-12abs ↗pdf ↗

We propose a new algorithm for Dehn surgery problem, finding exceptional Dehn filling slopes for a given hyperbolic 3-manifold with a torus boundary, using a quantum invariant called "3D index". The invariant is defined using an ideal triangulation of the cusped 3-manifold. We test the algorithm for many examples.

2018-03-29abs ↗pdf ↗

DreamFusion uses text-to-image diffusion models to create 3D images efficiently.

problem Lack of large-scale 3D datasets and efficient architectures for 3D synthesis.
method Adapting a 2D diffusion model to 3D synthesis using a loss based on probability density distillation.
result A 3D model can be optimized from a 2D diffusion model, allowing for text-to-3D synthesis.

Highly expressive models such as deep neural networks (DNNs) have been widely applied to various applications. However, recent studies show that DNNs are vulnerable to adversarial examples, which are carefully crafted inputs aiming to mislead the predictions. Currently, the majority of these studies have focused on per…

2018-10-11abs ↗pdf ↗

A neural atlas simplifies 3D geometry simulation by avoiding meshing.

problem Simulation of complex 3D geometries with thin features or non-trivial topology.
method Learned geometric representation of overlapping volumetric coordinate charts, trained from point-cloud or level-set data.
result The learned atlas enables different solvers without re-meshing or re-parametrization.