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.
Develops adaptive algorithms for sustainable fertilizer use in agriculture.
Classifies fertility of all rational links.
A knot is fertile if it can generate all smaller knots through a specific diagram modification.
The article presents a new non-parametric approach for forecasting mortality and fertility using Gaussian process regression.
Even knots with more than 30 crossings are not fertile.
Data mining involves the systematic analysis of large data sets, and data mining in agricultural soil datasets is exciting and modern research area. The productive capacity of a soil depends on soil fertility. Achieving and maintaining appropriate levels of soil fertility, is of utmost importance if agricultural land i…
In this paper, we introduce a new type of relation between knots called the descendant relation. One knot is a descendant of another knot if can be obtained from a minimal crossing diagram of by some number of crossing changes. We explore properties of the descendant relation and study how certain knots…
The paper studies vector bundles over surfaces, focusing on singularity formation.
Precision farming uses data analysis to optimize crop management.
Understanding and accurately predicting within-field spatial variability of crop yield play a key role in site-specific management of crop inputs such as irrigation water and fertilizer for optimized crop production. However, such a task is challenged by the complex interaction between crop growth and environmental and…
We present, solve and numerically simulate a simple model that describes the consequences of increased longevity on fertility rates, population growth and the distribution of wealth in developed societies. We look at the consequences of the repeated use of life extension techniques and show that they represent a novel …
Counterfactuals help compare different scenarios in CI and XAI.
SAGDA generates synthetic agricultural datasets to improve ML in African farming.
A statistical analysis of financial, economic, and demographic indicators performed by the authors demonstrates (1) that the main countries of East Africa (Uganda, Kenya, and Tanzania) have not escaped the Malthusian Trap yet; (2) that this countries are not likely to follow the "North African path" and to achieve this…
Paper predicts embryo implantation probability from IVF time-lapse imaging.
This paper reviews bank performance determinants, highlighting future research areas.
Tens of millions of women suffer from infertility worldwide each year. In vitro fertilization (IVF) is the best choice for many such patients. However, IVF is expensive, time-consuming, and both physically and emotionally demanding. The first question that a patient usually asks before the IVF is how likely she will co…
Econophysics embodies the recent upsurge of interest by physicists into financial economics, driven by the availability of large amount of data, job shortage in physics and the possibility of applying many-body techniques developed in statistical and theoretical physics to the understanding of the self-organizing econo…
Paper introduces a new model for cyber insurance pricing.
This paper reviews deep learning and knowledge-based methods for molecular design.
Improved prediction of soil parameters using Multi-target Stacked Generalisation on EDXRF spectra.
This paper focuses on a class of linear Hawkes processes with general immigrants. These are counting processes with shot noise intensity, including self-excited and externally excited patterns. For such processes, we introduce the concept of age pyramid which evolves according to immigration and births. The virtue if t…
We introduce a program aimed to studying problems arising from the theory of complex networks with differential geometric means. We study the propagation of influences on manifolds assuming that at each point only a finite number of propagation velocities are allowed. This leads to the computation of the volume of the …
The common view that our creativity is what makes us uniquely human suggests that incorporating research on human creativity into generative deep learning techniques might be a fruitful avenue for making their outputs more compelling and human-like. Using an original synthesis of Deep Dream-based convolutional neural n…
We introduce a multivariate Hawkes process with constraints on its conditional density. It is a multivariate point process with conditional intensity similar to that of a multivariate Hawkes process but certain events are forbidden with respect to boundary conditions on a multidimensional constraint variable, whose evo…
The graphics processing unit (GPU) has emerged as a powerful and cost effective processor for general performance computing. GPUs are capable of an order of magnitude more floating-point operations per second as compared to modern central processing units (CPUs), and thus provide a great deal of promise for computation…
New -algebra approach unifies machine learning strategies.
This paper explores portfolio management strategies to maximize alpha and minimize beta.
Given the recent surge in developments of deep learning, this article provides a review of the state-of-the-art deep learning techniques for audio signal processing. Speech, music, and environmental sound processing are considered side-by-side, in order to point out similarities and differences between the domains, hig…
Aggregated data is commonplace in areas such as epidemiology and demography. For example, census data for a population is usually given as averages defined over time periods or spatial resolutions (cities, regions or countries). In this paper, we present a novel multi-task learning model based on Gaussian processes for…
Paper introduces a framework for managing cyber risk with insurance and cybersecurity models.
Self-supervised learning helps train deep features without needing lots of labeled data.
The basic financial purpose of a firm is to maximize its value. An inventory management system should also contribute to realization of this basic aim. Many current asset management models currently found in financial management literature were constructed with the assumption of book profit maximization as basic aim. H…
Study finds Indian mutual funds adjust cash holdings based on inflows, impacting stock purchases.
Variational quantum computing faces a flat optimization landscape problem.
Framework for managing cyber risks in networks.
Product reviews and ratings on e-commerce websites provide customers with detailed insights about various aspects of the product such as quality, usefulness, etc. Since they influence customers' buying decisions, product reviews have become a fertile ground for abuse by sellers (colluding with reviewers) to promote the…
Research identifies risks in selecting project managers for civil engineering projects.
Deep learning improves portfolio management by optimizing asset weights.
This research develops a dynamic risk management system for industrial companies.
Study finds managers' tenure and education influence their choice between in-court and out-of-court restructuring.
The paper fits cash management models to data using stochastic and linear programming.
Since the advent of the horseshoe priors for regularization, global-local shrinkage methods have proved to be a fertile ground for the development of Bayesian methodology in machine learning, specifically for high-dimensional regression and classification problems. They have achieved remarkable success in computation, …
Decision tool helps manage biofouling risks for ships in the Baltic Sea.
Model cash management under ambiguity using maxmin preferences and diffusion.
New method for reducing dimensions of distributional data.
This review classifies electricity price models for risk management.
Study improves machine learning for long-term financial portfolio management.