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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.

168,742 papers · 148 categories

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5101520 · Jul 202019922001200920172026
48 results for cortical folding

Paper proposes a method to compare vector fields across surfaces, useful for analyzing brain folding patterns.

problem Comparing vector fields across surfaces of different geometries is challenging.
method The paper introduces a framework to transport vector fields onto a common space using differential geometry.
result The proposed framework enables the computation of statistics on vector fields, demonstrating its effectiveness in analyzing brain folding patterns.

Cortical circuits exhibit intricate recurrent architectures that are remarkably similar across different brain areas. Such stereotyped structure suggests the existence of common computational principles. However, such principles have remained largely elusive. Inspired by gated-memory networks, namely long short-term me…

2017-11-07abs ↗pdf ↗

Biological neural network mimics CCA for multi-channel data.

problem Implementing CCA in a biologically plausible neural network.
method Derive an online CCA algorithm with local synaptic updates for multi-compartmental neurons.
result The derived neural network architecture and synaptic updates resemble cortical pyramidal neuron behavior.

Improves MRI-based brain surface reconstruction with minimal deformation energy loss.

problem Ensuring optimal deformation energy and consistency in learning-based cortical surface reconstruction.
method Design and implementation of a Minimal Energy Deformation (MED) loss in the V2C-Flow model.
result Significant improvements in training consistency and reproducibility without sacrificing reconstruction accuracy and topological correctness.

Neural networks learn to mimic brain neurons with two-input activation functions, improving performance and robustness.

problem Training neural networks to mimic the complex interactions of brain neurons.
method Developed a network-in-network architecture with two-input activation functions, optimized hyperparameters, and compared to conventional ReLU networks.
result Two-input activation functions can learn soft XOR functions, improving network performance and robustness.

The paper develops models to understand sensory coding and cortical topography.

problem Understanding how visual cortical areas' receptive fields and topographic maps relate to environmental statistical structure.
method Energy-based models applied to probability density estimation, constrained by biological constraints.
result The models qualitatively reproduce receptive field and map properties found in vivo.

This work optimizes reservoir computing models by linking recurrence and non-linear dynamics.

problem Understanding how recurrence and non-linear dynamics in cortical networks contribute to their function.
method Transformed time-continuous, recurrent dynamics into an effective feed-forward structure of linear and non-linear temporal kernels.
result Optimal time-series classifiers can be built from random reservoir networks, demonstrating significant performance gains.

V1 cortex reconstructs images as Poisson equation solutions with varying weights.

problem Reconstructing images from V1 cortical cell receptive profiles.
method Solves a heterogeneous Poisson equation with varying weights representing neural connectivity.
result Reconstructions converge to homogeneous solutions using homogenization techniques.

New method aligns brain data across individuals for better brain decoding.

problem Inter-individual variability in brain response patterns limits decoder generalization.
method SpectralOT method that embeds cortical geometry into Laplace-Beltrami eigenmodes.
result SpectralOT strikes balance between aligning functional features and preserving anatomical structure.

The visual systems of many mammals, including humans, is able to integrate the geometric information of visual stimuli and to perform cognitive tasks already at the first stages of the cortical processing. This is thought to be the result of a combination of mechanisms, which include feature extraction at single cell l…

2014-07-02abs ↗pdf ↗

Gaudy images help train deep neural networks with less data.

problem Training deep neural networks with limited real data from visual cortex neurons.
method Used high-contrast binarized natural images (gaudy images) to train DNNs.
result Reduced training data needed for accurate DNN predictions of visual cortex neuron responses.

Machine learning for ASD diagnosis using morphological MRI networks.

problem Challenging to diagnose ASD using MRI due to heterogeneity and incomplete network neuroscience.
method Crowdsourced Kaggle competition to develop and benchmark ML pipelines.
result First-ranked team achieved 70% accuracy, 72.5% sensitivity, and 67.5% specificity.

Model explains optical illusions using geometric sub-Riemannian geodesics.

problem Understanding and explaining geometrical optical illusions.
method Neuro-mathematical model based on sub-Riemannian geodesics in the Roto-Translation Group.
result Illusory contours are described as geodesics in a new metric.

VNNs transfer well across datasets for brain age prediction using cortical thickness features.

problem Predicting brain age using anatomical features.
method Transferability of coVariance neural networks (VNNs) in brain age prediction.
result VNNs can assign anatomical interpretability to elevated brain age gap in AD.

The paper relaxes constraints on predictive coding models, making them more biologically plausible.

problem Neurophysiological models of predictive coding are not fully biologically plausible.
method The paper relaxes constraints on standard predictive coding algorithms by removing neurally implausible features.
result The removal of neurally implausible features does not significantly affect learning performance.

Causal inference concerns the identification of cause-effect relationships between variables, e.g. establishing whether a stimulus affects activity in a certain brain region. The observed variables themselves often do not constitute meaningful causal variables, however, and linear combinations need to be considered. In…

2015-12-03abs ↗pdf ↗

Deep learning has recently led to great successes in tasks such as image recognition (e.g Krizhevsky et al., 2012). However, deep networks are still outmatched by the power and versatility of the brain, perhaps in part due to the richer neuronal computations available to cortical circuits. The challenge is to identify …

2013-12-20abs ↗pdf ↗

We prove the existence of asymptotically cylindrical (ACyl) Calabi-Yau 3-folds starting with (almost) any deformation family of smooth weak Fano 3-folds. This allow us to exhibit hundreds of thousands of new ACyl Calabi-Yau 3-folds; previously only a few hundred ACyl Calabi-Yau 3-folds were known. We pay particular att…

2012-06-11abs ↗pdf ↗

This is a survey paper of author's results on cobordism groups and semigroups of fold maps and simple fold maps. The results include: establishing a relation between fold maps and immersions through geometrical invariants of cobordism classes of fold maps and simple fold maps in terms of immersions with prescribed norm…

2007-09-04abs ↗pdf ↗

The elastic net was introduced as a heuristic algorithm for combinatorial optimisation and has been applied, among other problems, to biological modelling. It has an energy function which trades off a fitness term against a tension term. In the original formulation of the algorithm the tension term was implicitly based…

2011-08-14abs ↗pdf ↗

The paper proves the existence of a folded annulus with multiple creases.

problem Existence of a folded annulus with multiple creases.
method Analyze developable surfaces, use normal curvature and relative torsion, compute geometric descriptors, prove propagation of folds.
result Proves the existence of a folded annulus with multiple creases.

First steps towards a classification of irreducible symplectic 4-folds whose integral 2-cohomology with 4-tuple cup product is isomorphic to that of Hilb^2(K3). We prove that any such 4-fold deforms to an irreducible symplectic 4-fold of Type A or Type B. A 4-fold of Type A is a double cover of a (singular) sextic hype…

2005-04-21abs ↗pdf ↗

Paper revisits graph-CNNs using Laplace-Beltrami spectral filters and polynomials.

problem Improving spectral graph convolutional neural networks (graph-CNNs).
method Developed Laplace-Beltrami CNN (LB-CNN) by replacing graph Laplacian with LB operator and approximating spectral filters using Chebyshev, Laguerre, and Hermite polynomials.
result Classification accuracy of LB-CNN is not dependent on the type of polynomials or operators.

Upper bounds on ribbonlength of various knots, showing linear and sub-linear behavior.

problem Estimating the ribbonlength of different types of knots.
method Using Kauffman's model of folded ribbon knots, we derive upper bounds on ribbonlength for specific knot types.
result Upper bounds on ribbonlength are linear in crossing number for some knots and sub-linear for others.

New contact structures on folded sums of contact mapping tori are tight under certain conditions.

problem Understanding tight contact structures on folded sums of contact mapping tori.
method Alternative bundle-theoretical construction and gluing process near the fold.
result Folded contact structures on folded sums of contact mapping tori are tight under specific conditions.

Every oriented 4-manifold admits a folded symplectic structure, which in turn determines a homotopy class of compatible almost complex structures that are discontinuous across the folding hypersurface ("fold") in a controlled fashion. We define folded holomorphic maps, i.e. pseudo-holomorphic maps that are discontinuou…

2005-11-24abs ↗pdf ↗

A smooth map having only fold singularities is called a fold-map. We will give effective conditions for a continuous map to be homotopic to a fold-map from the viewpoint of the homotopy principle.

2003-09-08abs ↗pdf ↗

This paper explores non-periodic folding of Spidron units, revealing nonlinear dynamics.

problem Understanding the kinematics and nonlinear phenomena of Spidron units.
method Analysis of single unit cell kinematics and recursive construction of multiple cells.
result Non-periodic folding restricts isotropic folding as the number of unit cells increases.

A generic smooth map of a closed 2k2k-manifold into (3k1)(3k-1)-space has a finite number of cusps (Σ1,1Σ^{1,1}-singularities). We determine the possible numbers of cusps of such maps. A fold map is a map with singular set consisting of only fold singularities (Σ1,0Σ^{1,0}-singularities). Two fold maps are fold bordant if the…

2007-01-16abs ↗pdf ↗

New formulas for mean curvature of submanifolds in geometries with torsion.

problem Characterizing submanifolds in geometries with intrinsic torsion.
method Deriving formulas for mean curvature of associative, coassociative, and Cayley submanifolds.
result New obstructions to the local existence of coassociative 4-folds in G2-structures with torsion.

The study examines K-polystability on Fano 4-folds with specific Lefschetz defects.

problem Investigating K-polystability on Fano 4-folds with Lefschetz defect at least 2.
method Examining 19 families of Fano 4-folds with Lefschetz defect 3 and 175 families with Lefschetz defect 2, proving K-polystability and instability.
result Exactly 5 out of 19 families of Fano 4-folds with Lefschetz defect 3 are K-polystable, and 5 out of 175 Casagrande-Druel Fano 4-folds with Lefschetz defect 2 are K-polystable.