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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.

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48 results for Satellite Data

FedSpace optimizes ML training on satellites and ground stations.

problem Training machine learning models on satellites with limited bandwidth.
method Federated Learning framework that dynamically schedules model aggregation based on satellite orbits.
result Reduces training time by 1.7 days over state-of-the-art algorithms.

Modeling wildfire aerosols using satellite data to predict solar radiation reduction.

problem Accurately estimate and predict AOD propagation from wildfires using multi-source satellite data.
method Physics-informed statistical modeling integrating multi-source satellite data with an advection-diffusion equation.
result The proposed approach accurately predicts AOD propagation and demonstrates model interpretability.

In this paper, we construct two families of satellite constructions for Brunnian links, called the satellite sum and the satellite tie. An interesting fact is that by applying the satellite sum and the satellite tie constructions, we can build infinitely many new Brunnian links from any given Brunnian links. With the h…

2019-06-04abs ↗pdf ↗

Satellite imagery and ML improve livelihood measurements and estimate electrification's impact.

problem Sparse data hinders policy development and evaluation.
method Satellite imagery, machine learning, and ML inference techniques.
result Grid access improves rural asset wealth by 0.17 standard deviations.

This study analyzes satellite communication latency using a stochastic geometry model.

problem Latency analysis of LEO satellite relay communication systems.
method Stochastic geometry framework with spherical BPP models, suboptimal satellite relay selection strategy.
result Derives distance distributions and analytical expressions for transmission delays.

Any knot in a solid torus, called a pattern or satellite operator, acts on knots in the 3-sphere via the satellite construction. We introduce a generalization of satellite operators which form a group (unlike traditional satellite operators), modulo a generalization of concordance. This group has an action on the set o…

2013-06-19abs ↗pdf ↗

Estimates spatio-temporal data with satellite NO2 concentrations using Yule-Walker equations.

problem Estimating large spatio-temporal autoregressions with unknown spatial interactions.
method Sparse generalized Yule-Walker estimation, penalized regression, spatial and temporal dependence.
result Strong forecast improvements and evidence of spatial interactions in NO2 satellite data.

Space debris warnings follow a predictable pattern, allowing timely satellite maneuvers.

problem Estimating when fresh information about space debris will arrive.
method Statistical learning model of the message arrival process, specifically a Bayesian Poisson process.
result The average prediction error for the next message arrival time is smaller than baseline predictions.

Deep learning models perform variably across continents/seasons in land cover mapping.

problem Variability in deep learning model performance across different continents/seasons.
method Clustering techniques on satellite imagery from different continents.
result Model performance varies significantly between different continents/seasons.

Develops a new framework for integrating satellite allocations in small portfolios.

problem Feasibility constraints in small portfolios, not return predictability, are the primary concerns.
method A four-layer feasibility framework: physical, economic, structural, and epistemic.
result Closed-form feasibility bounds on satellite size, turnover, and breadth without return forecasts.

Satellite imagery helps adjust for unobserved confounders in observational studies.

problem Adjusting for confounding factors in observational studies with non-tabular data like satellite imagery.
method Formalizing conditions for causal effect identification, estimation, and sensitivity analysis.
result Demonstrated the use of satellite imagery as a proxy for unobserved confounders in anti-poverty aid programs.

Forest tree species mapped with high accuracy using satellite data.

problem Classifying dominant tree species in Swedish forests.
method Extreme gradient boosting model with Bayesian optimization, combining Sentinel-1/2 satellite data and field observations.
result Overall accuracy of 85%, F1 score of 0.82, Matthews correlation coefficient of 0.81.

New algorithms improve uncertainty estimation in satellite precipitation predictions.

problem Lack of uncertainty estimates in machine learning spatial precipitation predictions from satellite data.
method Benchmarked six algorithms including LightGBM, compared using quantile scoring functions and rules.
result LightGBM outperformed other algorithms in quantile scoring rule by 11.10%.

Probabilistic NDVI forecasting from sparse satellite data.

problem Challenges in short-term NDVI forecasting due to sparse and irregular satellite data.
method Probabilistic forecasting framework using historical NDVI and meteorological observations, with temporal-distance weighted quantile loss and extreme-weather feature engineering.
result The proposed method outperforms baselines on pointwise and probabilistic evaluation metrics.

The Gluck twist preserves the diffeomorphism type of certain satellite 2-knots.

problem Preserving the diffeomorphism type of satellite 2-knots under the Gluck twist.
method Using new descriptions of satellite 2-knots, the paper shows that the Gluck twist does not change the diffeomorphism type of certain satellite 2-knots in three ways.
result The Gluck twist preserves the diffeomorphism type of certain satellite 2-knots.

Techniques are introduced which determine the geometric structure of non-simple two-generator 33-manifolds from purely algebraic data. As an application, the satellite knots in the 33-sphere with a two-generator presentation in which at least one generator is represented by a meridian for the knot are classified.

1997-03-14abs ↗pdf ↗

Researchers compute Khovanov polynomials for satellite knots.

problem Computing Khovanov polynomials for satellite knots.
method Explicit computation using a computer program for two families of satellite knots.
result Khovanov polynomials can be expressed as a linear combination of pattern and companion invariants, with a jump at a critical point.

Necessary and sufficient conditions are given for a satellite knot to be fibered. Any knot k~\tilde k embeds in an unknotted solid torus V~\tilde V with arbitrary winding number in such a way that no satellite knot with pattern (V~,k~)(\tilde V, \tilde k) is fibered. In particular, there exist nonfibered satellite knots wit…

2007-04-30abs ↗pdf ↗

The study computes invariants of satellite knots using bordered Floer homology.

problem Computing invariants of satellite knots with specific patterns.
method Using bordered Floer homology and the immersed curve interpretation of the bordered pairing theorem.
result Satellites with thin fibered companions or specific patterns have thin knot Floer homology.

We conjecture that satellite operations are either constant or have infinite rank in the concordance group. We reduce this to the difficult case of winding number zero satellites, and use SO(3)SO(3) gauge theory to provide a general criterion sufficient for the image of a satellite operation to generate an infinite rank s…

2018-09-11abs ↗pdf ↗

The paper analyzes optimal overbetting strategies for a satellite investment account.

problem Optimal control of leverage in a satellite investment account with limited leverage.
method Recursive overbetting strategy to maximize growth rate, solved via HJB equation.
result Optimal overbetting strategy balances growth rate of satellite and composite bankroll.

Mutant knots, in the sense of Conway, are known to share the same Homfly polynomial. Their 2-string satellites also share the same Homfly polynomial, but in general their m-string satellites can have different Homfly polynomials for m>2. We show that, under conditions of extra symmetry on the constituent 2-tangles, the…

2007-05-09abs ↗pdf ↗

A cased-based reasoning method predicts rare events on strategic sites using satellite imagery.

problem Manual prediction of rare events on strategic sites is impractical due to large datasets.
method Case-based reasoning approach incorporating expert knowledge for irregular time series and small datasets.
result The method significantly outperforms random selection on challenging applications.