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.
We develop a new method to estimate failure probabilities in complex systems.
To a large extent, the systemic importance of financial institutions is related to the topology of financial liability networks. In this work we reconstruct and analyze the - to our knowledge - largest financial network that has been studied up to now. This financial liability network consists of 51,980 firms and 796 b…
Hyperbolic geometry reveals financial network structure and systemic importance.
Develops fair feature importance scores for tree-based models to interpret fairness.
New neural net learns time-reversible symplectic dynamics.
Paper proves a Cohen-Dimca-Orlik type theorem for Z-local systems of hyperplane arrangements.
As energy markets begin clearing at sub-hourly rates, their interaction with load control systems becomes a potentially important consideration. A simple model for the control of thermal systems using market-based power distribution strategies is proposed, with particular attention to the behavior and dynamics of elect…
We examine counterfactual explanations for explaining the decisions made by model-based AI systems. The counterfactual approach we consider defines an explanation as a set of the system's data inputs that causally drives the decision (i.e., changing the inputs in the set changes the decision) and is irreducible (i.e., …
Combining feature importance estimates improves reliability of machine learning predictions.
Modeling cascading behavior in complex systems using CTBNs.
In this research, we introduce a robust metric to identify Systemically Important Financial Institution (SIFI) in a financial network by taking into account both common idiosyncratic shocks and contagion through counterparty exposures. We develop an efficient algorithm to rank financial institutions by formulating a fi…
Proposes a method to ensure accurate estimation of rare events in AI systems.
Online retailers execute a very large number of price updates when compared to brick-and-mortar stores. Even a few mis-priced items can have a significant business impact and result in a loss of customer trust. Early detection of anomalies in an automated real-time fashion is an important part of such a pricing system.…
As machine learning systems move from computer-science laboratories into the open world, their accountability becomes a high priority problem. Accountability requires deep understanding of system behavior and its failures. Current evaluation methods such as single-score error metrics and confusion matrices provide aggr…
The blockchain technology promises to transform finance, money and even governments. However, analyses of blockchain applicability and robustness typically focus on isolated systems whose actors contribute mainly by running the consensus algorithm. Here, we highlight the importance of considering trustless platforms wi…
A new method estimates time-varying parameters in earth system models using offline and online data assimilation.
New method provides calibrated feature importance explanations for regression models.
The relationship between micro-structure and macro-structure of complex systems using information geometry has been dealt by several authors. From this perspective, we are going to apply it as a geometrical structure connecting both microeconomics and macroeconomics . The results lead us to introduce new modified quant…
In complex systems like financial market, risk tolerance of individuals is crucial for system resilience.The single-security price limit, designed as risk tolerance to protect investors by avoiding sharp price fluctuation, is blamed for feeding market panic in times of crash.The relationship between the critical market…
The numerical integration plays a fundamental role in understanding the behaviour of many mechanical systems. In this paper some important aspects of the mechanical integrators on the dynamics of a mechanical system are studied. More specific, we have shown that if that the Lie-Trotter integrator is obtained, in case o…
A new method for estimating probabilities and risks using Markov processes.
This study quantifies systemic importance in global banks using a continuous framework that amplifies localized shocks.
Data extracted from software repositories is used intensively in Software Engineering research, for example, to predict defects in source code. In our research in this area, with data from open source projects as well as an industrial partner, we noticed several shortcomings of conventional data mining approaches for c…
A formula for the Riemannian metric tensor of differentiable manifolds of linear dynamical systems of same McMillan degree is presented in terms of their transfer function matrices. The necessary calculations for its application to ARMA and state space overlapping parametrizations are drafted. The importance of this ap…
Artificial Intelligence (AI) systems sometimes make errors and will make errors in the future, from time to time. These errors are usually unexpected, and can lead to dramatic consequences. Intensive development of AI and its practical applications makes the problem of errors more important. Total re-engineering of the…
Financial networks are dynamic. To assess their systemic importance to the world-wide economic network and avert losses we need models that take the time variations of the links and nodes into account. Using the methodology of classical mechanics and Laplacian determinism we develop a model that can predict the respons…
Deep reinforcement learning method finds rare events in complex systems.
Study identifies personality traits from dance movements in music.
The study examines stability of Hamiltonian Poisson integrators on both integrable and non-integrable systems.
Paper develops Monte-Carlo estimators for CoVaR, a key risk measure.
New algorithm reduces costs in wind energy systems by minimizing decision changes.
This study prioritizes temporal resolution over spatial in energy systems models due to higher influence.
Study on Haantjes tensors for superintegrable systems, focusing on vanishing properties.
Spoken language translation (SLT) has become very important in an increasingly globalized world. Machine translation (MT) for automatic speech recognition (ASR) systems is a major challenge of great interest. This research investigates that automatic sentence segmentation of speech that is important for enriching speec…
We provide a thorough construction of a system of compatible determinant line bundles over spaces of Fredholm operators, fully verify that this system satisfies a number of important properties, and include explicit formulas for all relevant isomorphisms between these line bundles. We also completely describe all possi…
Interpretation of electroencephalogram (EEG) signals can be complicated by obfuscating artifacts. Artifact detection plays an important role in the observation and analysis of EEG signals. Spatial information contained in the placement of the electrodes can be exploited to accurately detect artifacts. However, when few…
Paper introduces OARF benchmark suite for federated learning systems.
EPGP priors solve linear PDEs from data.
PCCs combine PCA and copulas for high-dimensional tail dependence modeling.
Paper speeds up policy optimization for large recommendation systems.
Deep-PrAE improves rare-event simulation for black-box systems.
The study explores autonomous systems and their connections to contact geometry and Frobenius manifolds.
Proposes a credit scoring system for Aave accounts.
This paper discusses e-commerce integration with SAP for Turkish businesses.
New approach to -dimensional torus differential equations.
We show uniqueness of cylindrical blowups for mean curvature flow in all dimension and all codimension. Cylindrical singularities are known to be the most important; they are the most prevalent in any codimension. Mean curvature flow in higher codimension is a nonlinear parabolic system where many of the methods used f…
Before A/B testing online a new version of a recommender system, it is usual to perform some offline evaluations on historical data. We focus on evaluation methods that compute an estimator of the potential uplift in revenue that could generate this new technology. It helps to iterate faster and to avoid losing money b…
CG-BGs combine flow-based models with PMFs to sample large systems efficiently.