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.
DCE learns customer embeddings from digital activity and financial context.
SFC aims to protect the Amazon with a digital currency and smart contracts.
We determine the price of digital double barrier options with an arbitrary number of barrier periods in the Black-Scholes model. This means that the barriers are active during some time intervals, but are switched off in between. As an application, we calculate the value of a structure floor for structured notes whose …
New method predicts political ideology from online activity.
Study shows monetary policy impacts digital assets like BTC and ETH.
Digital tools may hinder or facilitate multidisciplinary collaboration in occupational health.
CNN identifies AGN host galaxies from Sloan Digital Sky Survey data.
The digital revolution of the banking system with evolving European regulations have pushed the major banking actors to innovate by a newly use of their clients' digital information. Given highly sparse client activities, we propose CPOPT-Net, an algorithm that combines the CP canonical tensor decomposition, a multidim…
Research identifies four motivational groups for crypto-metaverse landowners.
The production and consumption of information about Bitcoin and other digital-, or 'crypto'-, currencies have grown together with their market capitalisation. However, a systematic investigation of the relationship between online attention and market dynamics, across multiple digital currencies, is still lacking. Here,…
Study examines European banks' digital transformation strategies.
Two new approaches improve decision-making in asset monitoring systems.
What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we foc…
Social media enhances or diminishes scientific status, depending on usage.
Agent decides when to measure latent states in RL to improve efficiency.
FTX's failure linked to Terra-Luna collapse and Binance's influence.
Common nonlinear activation functions used in neural networks can cause training difficulties due to the saturation behavior of the activation function, which may hide dependencies that are not visible to vanilla-SGD (using first order gradients only). Gating mechanisms that use softly saturating activation functions t…
KLD token adjusts supply based on macroeconomic debt index, creating deflationary effect.
This paper is the first attempt to formalize a new field of economics; studding the Intangibles Goods available on the Internet. We are taking advantage of the digital world's specific rules, in particular the zero marginal cost, to propose a theory of trading & sharing unified. A function based money is created as a w…
Deep learning is still not a very common tool in speaker verification field. We study deep convolutional neural network performance in the text-prompted speaker verification task. The prompted passphrase is segmented into word states - i.e. digits -to test each digit utterance separately. We train a single high-level f…
Extracting automatically the complex set of features composing real high-dimensional data is crucial for achieving high performance in machine--learning tasks. Restricted Boltzmann Machines (RBM) are empirically known to be efficient for this purpose, and to be able to generate distributed and graded representations of…
In this paper, a novel architecture of Recurrent Neural Network (RNN) is designed and experimented. The proposed RNN adopts a computational memory based on the concept of stigmergy. The basic principle of a Stigmergic Memory (SM) is that the activity of deposit/removal of a quantity in the SM stimulates the next activi…
Analysis of log data generated by online educational systems is an essential task to better the educational systems and increase our understanding of how students learn. In this study we investigate previously unseen data from Clio Online, the largest provider of digital learning content for primary schools in Denmark.…
In the last decade, the digital age has sharply redefined the way we study human behavior. With the advancement of data storage and sensing technologies, electronic records now encompass a diverse spectrum of human activity, ranging from location data, phone and email communication to Twitter activity and open-source c…
Machine learning predicts COVID-19 activity in China.
The yearly aggregated tax income data of all, more than 8000, Italian municipalities are analyzed for a period of five years, from 2007 to 2011, to search for conformity or not with Benford's law, a counter-intuitive phenomenon observed in large tabulated data where the occurrence of numbers having smaller initial digi…
Digital money could reduce germ spread during coronavirus.
We consider the at-the-money strike derivative of implied volatility as the maturity tends to zero. Our main results quantify the behavior of the slope for infinite activity exponential Lévy models including a Brownian component. As auxiliary results, we obtain asymptotic expansions of short maturity at-the-money digit…
Handwriting disorder (termed dysgraphia) is a far from a singular problem as nearly 8.6% of the population in France is considered dysgraphic. Moreover, research highlights the fundamental importance to detect and remediate these handwriting difficulties as soon as possible as they may affect a child's entire life, und…
The DAO Report led to a significant shift of ICO activity to Europe.
Study of digital topology concepts like hyperspaces and function graphs.
The paper highlights issues with fixed point claims in digital images.
Study of urban lifestyles from mobility data of 1.2M people in 11 U.S. cities.
Find limiting sets for digital cones and suspensions.
Corrects incorrect assertions about fixed points in digital topology.
Study AFPP of unions of convex digital disks in 2D.
The paper addresses flaws in fixed point assertions for digital images.
Study minimal freezing sets in convex digital disks.
A model of associative memory is studied, which stores and reliably retrieves many more patterns than the number of neurons in the network. We propose a simple duality between this dense associative memory and neural networks commonly used in deep learning. On the associative memory side of this duality, a family of mo…
Study on cold and freezing sets in digital images.
Conventional modeling approaches have found limitations in matching the increasingly detailed neural network structures and dynamics recorded in experiments to the diverse brain functionalities. On another approach, studies have demonstrated to train spiking neural networks for simple functions using supervised learnin…
Incorrect fixed point assertions in digital topology are discussed.
In this paper, we show how to construct graph theoretical models of n-dimensional continuous objects and manifolds. These models retain topological properties of their continuous counterparts. An LCL collection of n-cells in Euclidean space is introduced and investigated. If an LCL collection of n-cells is a cover of a…
Incorrect fixed point assertions in digital topology are discussed.
Redundancy in deep neural network (DNN) models has always been one of their most intriguing and important properties. DNNs have been shown to overparameterize, or extract a lot of redundant features. In this work, we explore the impact of size (both width and depth), activation function, and weight initialization on th…
Digital trees have approximate fixed point property, and conditions for products are explored.
Study convexity and AFPP in digital images.
Study uses web search data to analyze tech startups growth.