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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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48 results for marine biology

The paper improves marine buoy placement to detect ships robustly against disruptions.

problem Detecting fishing vessels in the presence of natural and man-made disruptions.
method Formulated as a clustering problem, used dropout k-means and k-median to improve buoy placement robustness.
result Improved ship detection probability with dropout k-means compared to classic methods.

Framework improves marine mammal monitoring in noisy underwater environments.

problem Underwater bioacoustic monitoring challenges due to overlapping calls and variable noise.
method Multi-step attention-guided framework with segmentation and mid-level fusion.
result Improved signal discrimination, reduced false positives, reliable representations.

Machine learning models predict bluebottles' presence on beaches, addressing class imbalance and unreliable absence data.

problem Predicting bluebottles' presence on beaches with machine learning, tackling class imbalance and unreliable absence data.
method Used Multilayer Perceptron, Random Forest, and XGBoost models; employed data augmentation techniques like SMOTE, Random Undersampling, and Synthetic Negative Approach.
result Random Forests combined with Synthetic Negative Approach provided the best predictive model, identifying wind direction as a key factor.

Extends Shifts dataset for MS lesion segmentation and marine vessel power estimation.

problem Distributional shift in training and deployment data for ML models.
method Develops new datasets for high-risk industrial applications.
result Demonstrates robustness and uncertainty estimation in new industrial tasks.

We show that up to automorphisms of PC2\mathbb{P}^2_{\mathbb C} there are 55 homogeneous convex foliations of degree four on PC2.\mathbb{P}^2_{\mathbb C}. Using this result, we give a partial answer to a question posed in 20132013 by D. {Marín} and J. {Pereira} about the classification of reduced convex foliations on~$\mat…

2018-11-16abs ↗pdf ↗

DECAT framework evaluates multimodal models for shared biology, detecting confounders and false positives.

problem Determining if multimodal models learn shared biology or just confounders.
method DECAT framework classifies multimodal representations into four diagnostic scenarios using null-referenced metrics.
result DECAT detects confounders and false positives in multimodal models, improving with larger cohorts and stronger representations.

P. Arnoux and A. Marin showed that any triangulation of RPn\mathbb{RP}^n contains more than (n+1)(n+2)2\frac{(n+1)(n+2)}{2} vertices if n3n \geq 3. We construct some natural triangulation of RPn\mathbb{RP}^n with n(n+5)21\frac{n(n+5)}{2}-1 vertices for all n3n \geq 3. Previously, it was known that RPn\mathbb{RP}^n has Z2n\mathbb{Z}_2^n-e…

2014-03-02abs ↗pdf ↗

Let n3n \geq 3. In this paper, we study the problem of whether a given finite group GG embeds in a quotient of the form Bn/Γk(Pn)B_n/Γ_k(P_n), where BnB_n is the nn-string Artin braid group, k{2,3}k \in \{2, 3\}, and {Γl(Pn)}lN\{Γ_l(P_n)\}_{l\in \mathbb{N}} is the lower central series of the nn-string pure braid group PnP_n. Previous …

2018-05-29abs ↗pdf ↗

The paper develops sampling methods for ocean phenomena based on temperature and salinity measurements.

problem Improving oceanographic sampling with limited resources.
method Design criterion based on uncertainty in excursions of vector-valued Gaussian random fields.
result Demonstrates effective exploration of ambiguous regions for data-driven sampling.

Two simulation-based methods improve optimal sampling design in systems biology.

problem Optimal selection of sampling points for accurate parameter estimation in dynamical systems.
method E-optimal-ranking (EOR) and LSTM neural network-based methods.
result Simulation studies show the proposed methods outperform random selection and classical E-optimal design.

Machine learning monitors detect motor overheating, adapting to concept drift.

problem Early detection of motor overheating in ships' propulsion systems.
method Machine learning and statistical methods using historical data to adapt to concept drift.
result The proposed monitors provide early detection of overheating during and after concept drifts.

Flexible XVAE model for efficient spatial extremes simulation.

problem Complex tail dependence structures in spatial extremes processes.
method Variational autoencoder (XVAE) for modeling flexible and non-stationary dependence.
result XVAE provides fast inference and outperforms traditional models in high dimensions.

This review assesses statistical and machine learning methods for coral bleaching.

problem Coral bleaching due to rising sea temperatures and environmental factors.
method Statistical and machine learning models for predicting and analyzing coral bleaching.
result Statistical and machine learning methods are crucial for effective reef management.

A scalable Bayesian inference method for mixed-effects models in systems biology.

problem Scalable Bayesian inference for complex hierarchical mixed-effects models in systems biology.
method Constructing amortized approximations of likelihood and posterior distributions, refined for each individual dataset.
result Our method is both fast and competitive in statistical accuracy compared to exact pseudomarginal Bayesian inference.

Paper develops a neural-fuzzy controller for GPS-intelligent buoys.

problem Optimally track dynamically positioned marine buoys with unknown parameters.
method Dynamic system modeling using neural-fuzzy networks with backstepping technique.
result The controller minimizes position errors and adjusts buoy positions accurately.

We develop obstructions to a knot K in the 3-sphere bounding a smooth punctured Klein bottle in the 4-ball. The simplest of these is based on the linking form of the 2-fold branched cover of the 3-sphere branched over K. Stronger obstructions are based on the Ozsvath-Szabo correction term in Heegaard-Floer homology, al…

2010-05-29abs ↗pdf ↗

hyperSBINN improves drug cardiosafety assessment by efficiently modeling cardiac action potentials.

problem Complexity and limited data in modeling cardiac effects of drugs.
method Combining meta-learning with SBINNs to solve parameterized cardiac action potential models.
result hyperSBINN outperforms traditional solvers in speed and accuracy for predicting APD90 values.

BioBO optimizes gene perturbation design using Bayesian optimization with biological priors.

problem Efficient design of genomic perturbation experiments in drug discovery.
method Integrates Bayesian optimization with multimodal gene embeddings and enrichment analysis.
result Improves labeling efficiency by 25-40% and identifies top-performing perturbations more effectively.

We show that up to automorphisms of PC2\mathbb P^2_{\mathbb C} there are 1414 homogeneous convex foliations of degree 55 on PC2.\mathbb P^2_{\mathbb C}. We establish some properties of the Fermat foliation F0d\mathcal F_{0}^{d} of degree d2d\geq2 and of the Hilbert modular foliation FH5\mathcal{F}_H^{5} of degree 5.5. As a…

2018-12-22abs ↗pdf ↗

New algorithm optimizes matrix reordering for noisy disordered matrices.

problem Optimizing matrix reordering for noisy disordered matrices in single-cell biology and metagenomics.
method Proposed a polynomial-time adaptive sorting algorithm to improve upon spectral seriation.
result Our algorithm achieves superior performance compared to existing methods in real datasets.