Modeling how network connectivity affects economic collapse and robustness.
problem Impact of network topology on systemic risk and collapse of complex economic systems.
method Proposed a model to study the effects of network structure on economic systems by varying connectivity.
result Emergent systemic risks arise with increased interconnections, leading to phase transitions and tipping points.
New product structures encode superintegrable Hamiltonian systems in Euclidean spaces.
problem Encoding superintegrable Hamiltonian systems using product structures.
method Introducing commutative and associative product structures on Euclidean spaces of dimension at least three, satisfying specific conditions.
result All abundant superintegrable Hamiltonian systems on Euclidean space of dimension at least three arise from these product structures.
Python tool assesses European agricultural production resilience.
problem Estimating resilience of European agricultural production systems.
method Python software to compute annual production resilience indicator.
result Demonstrates resilience of European agricultural production.
A neural network method estimates entropy production from system trajectories.
problem Estimating entropy production from system trajectories without detailed dynamics.
method Developed a neural estimator (NEEP) for entropy production (EP).
result NEEP rigorously proves to provide stochastic EP by optimizing an objective function.
In e-commerce, content quality of the product catalog plays a key role in delivering a satisfactory experience to the customers. In particular, visual content such as product images influences customers' engagement and purchase decisions. With the rapid growth of e-commerce and the advent of artificial intelligence, tr…
E-commerce system predicts customer interest in sequentially ordered products.
problem Modeling customer interest in sequentially ordered products.
method Embed purchased items with Word2Vec and model the sequence with LSTM RNN.
result The recommender system outperforms its predecessor in click-through rate.
Tax systems ensure sustainable economic development by adjusting production technologies and gross output volumes.
problem Ensuring sustainable economic development through optimal tax systems.
method Explicit formulas and mathematical proofs for tax systems based on production technologies and gross output volumes.
result The vector of gross output must belong to the interior of the cone formed by the columns of the total cost matrix under perfect taxation systems.
This paper tackles hidden technical debts in fair ML systems for Fintech.
problem Building fair machine learning systems in financial services.
method Examining key stages of ML system development and deployment.
result Technical debts exist in deploying fair ML systems in Fintech.
Automated method selects best model from many for production systems.
problem Selecting the best model for production systems from a large pool.
method Automated online experimentation mechanism using Bayesian surrogate models.
result Efficiently identifies the best model with small online experiments.
Study shows how firms adapt to systemic risk during crises, revealing key players and trade volume predictors.
problem Understanding systemic risk in local production networks during crises.
method Analyzing Hungarian production network dynamics from 2015 to 2022 using a null model and empirical data.
result Firms' adaptive behavior during crises leads to more resilient economies, with trade volume being a significant predictor.
We propose an explicit construction of the deformation quantization of the general second-class constrained system, which is covariant with respect to local coordinates on the phase space. The approach is based on constructing the effective first-class constraint (gauge) system equivalent to the original second-class o…
This paper considers control systems defined on Lie algebroids. After deriving basic controllability tests for general control systems, we specialize our discussion to the class of mechanical control systems on Lie algebroids. This class of systems includes mechanical systems subject to holonomic and nonholonomic const…
Paper introduces RTT2Vec for real-time grocery recommendations, achieving 9.4% uplift over baselines.
problem Personalized grocery recommendations to improve user experience and sales.
method RTT2Vec deep architecture for real-time recommendations, approximate inference technique.
result 9.4% uplift in prediction metrics over baseline models.
Model assesses how supply chain disruptions affect financial stability.
problem Systemic risk in production networks and its financial implications.
method Data-driven econo-financial stress-testing framework combining supply chain and interbank networks.
result Increase of up to 28% in financial systemic risk due to production network contagion.
The hierarchical structure of production planning has the advantage of assigning different decision variables to their respective time horizons and therefore ensures their manageability. However, the restrictive structure of this top-down approach implying that upper level decisions are the constraints for lower level …
Productions functions map the inputs of a firm or a productive system onto its outputs. This article expounds generalizations of the production function that include state variables, organizational structures and increasing returns to scale. These extensions are needed in order to explain the regularities of the empiri…
Derives fluctuation theorems and thermodynamic uncertainty relations for systems modeled as Bayes nets.
problem Entropy production in interacting systems modeled as Bayes nets.
method Derives fluctuation theorems and thermodynamic uncertainty relations for arbitrary sets and conditioned sets of systems in Bayes nets.
result Relates the entropy production of the overall system to the precisions of probability currents in individual systems.
The paper optimizes exceptions in a statistical production system using machine learning.
problem Lack of curated and labeled training data for machine learning in data quality assurance.
method Explainable supervised machine learning to identify and prioritize exceptions.
result Improvement in the quality and efficiency of exceptions generated and authenticated by users.
Proposes CEP to better represent financial products' carbon impact.
problem Binary 'Green' label inadequately represents financial products' carbon impact.
method Introduces Carbon Equivalence Principle (CEP) for financial products.
result Financial products' carbon impact can be included as a linked term sheet.
Detects anomalies in product health metrics at eBay for better alerts.
problem Detecting anomalies in unsupervised product health metrics at eBay.
method Developed a Moving Metric Detector (MMD) for anomaly detection and a point-wise ranking model for alert retrieval.
result Improves alert precision and avoids alert spamming in eBay production.
Developed text classification system for Azerbaijani language.
problem Text clustering problem in Azerbaijani language.
method Machine learning and embedding techniques.
result System successfully categorizes news, product reviews, and more.
New method learns stochastic thermodynamics from system currents.
problem Understanding entropy production in complex dynamical systems.
method Constructs learning framework using currents and machine learning loss functions.
result Derives loss functions for thermodynamic functions directly from dynamics.
The authors characterize flexibility in power and energy markets considering time, spatiality, resource, and risk.
problem Evaluating and maximizing flexibility in power systems and markets.
method Characterization of flexibility dimensions (time, spatiality, resource, risk) and their interrelations with flexibility assets, products, and services.
result Flexibility should be evaluated based on multiple dimensions for efficient power systems and markets.
Electrostatic systems with specific tensors are locally conformally flat.
problem Understanding the geometry of electrostatic systems with special tensors.
method Proving local conformal flatness for electrostatic manifolds with divergence-free Bach tensor.
result Three-dimensional electrostatic manifolds with divergence-free Bach tensor are locally conformally flat.
In this paper we study the space of solutions to an overdetermined linear system involving the Hessian of functions. We show that if the solution space has dimension greater than one, then the underlying manifold has a very rigid warped product structure. We obtain a uniqueness result for prescribing the Ricci curvatur…
SPPL simplifies probabilistic programming for exact inference.
problem Efficient exact inference in probabilistic models.
method SPPL translates probabilistic programs into sum-product expressions, leveraging new techniques for scalability.
result SPPL achieves up to 3500x speedups in exact inference.
In this paper we analyse the bipartite Colombian firms-products network, throughout a period of five years, from 2010 to 2014. Our analysis depicts a strongly modular system, with several groups of firms specializing in the export of specific categories of products. These clusters have been detected by running the bipa…
The paper explores rigidity and proximality in dynamical systems, proving new results about C∗-algebras.
problem Understanding rigidity and proximality in dynamical systems and their algebraic counterparts.
method Analyzing crossed products of dynamical systems and their C∗-algebras, focusing on uniform rigidity and proximality. result Uniformly rigid systems are almost reflecting, and certain crossed products are reflecting.
Every year, thousands of people receive consumer product related injuries. Research indicates that online customer reviews can be processed to autonomously identify product safety issues. Early identification of safety issues can lead to earlier recalls, and thus fewer injuries and deaths. A dataset of product reviews …
The problem of ranking is a multi-billion dollar problem. In this paper we present an overview of several production quality ranking systems. We show that due to conflicting goals of employing the most effective machine learning models and responding to users in real time, ranking systems have evolved into a system of …
Study uses TDA to improve OEE forecasting in manufacturing.
problem Volatility and nonlinearity in OEE time series data.
method Topological Data Analysis (TDA) to transform raw data into structured knowledge.
result Improves OEE forecasting accuracy by at least 17%.
The symmetric product of vector fields on a manifold arises when one studies the controllability of certain classes of mechanical control systems. A geometric description of the symmetric product is provided using parallel transport, along the lines of the flow interpretation of the Lie bracket. This geometric interpre…
System interprets complex treatment effects for personalized policies.
problem Complex, hard-to-understand treatment effect models.
method Scalable, interpretable personalized experimentation system.
result Learned explanations and generated interpretable policies.
Coupled nonlinear integrable systems are generated from usual zero curvature equation. The relevant Maurer-Cartan forms are constructed by combining suitably chosen matrices (nilpotent, Hadamard, idempotent and k-idempotent) and Lie algebraic elements via Kronecker product. In each case a closure type property among th…
Adaptive time decay functions improve financial product recommendation accuracy.
problem Inaccurate recommendations due to static historical data in finance.
method Time-dependent collaborative filtering with personalized decay functions.
result Significant improvements over state-of-the-art benchmarks in financial product recommendation.
Predicting the future evolution of complex systems is one of the main challenges in complexity science. Based on a current snapshot of a network, link prediction algorithms aim to predict its future evolution. We apply here link prediction algorithms to data on the international trade between countries. This data can b…
Researchers infer firm-level supply chain networks from sector-level data to assess systemic risk.
problem Estimating systemic risk in economic systems using firm-level data.
method Maximum-entropy algorithms applied to input-output tables and firm-level aggregate output data.
result The most realistic systemic risk content is retrieved by models incorporating disaggregated firm-specific inputs by sector.
New superintegrable systems derived from Frobenius structures.
problem Constructing second-order superintegrable systems.
method Using conification and direct product construction, applying to semi-simple and nilpotent algebras.
result Explicitly constructed second-order superintegrable systems in three dimensions.
Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries' d…
We study quantum moment maps of G-invariant star products, which are a quantum analogue of the moment map for classical Hamiltonian systems. Introducing an integral representation, we show that any quantum moment map for a G-invariant star product is differentiable. This property gives us a new method for the class…
This communication is based on an original approach linking economical factors to technical and methodological ones. This work is applied to the decision process for mix production. This approach is relevant for costing driving systems. The main interesting point is that the quotation factors (linked to time indicators…
New method quantifies systemic risk of firms in supply networks.
problem Quantifying economic systemic risk of firms from supply networks.
method Unique value-added tax dataset; novel approach for computing ESR.
result A tiny fraction of companies have high systemic risk impacting 23% of national production.
We develop a complexity measure for large-scale economic systems based on Shannon's concept of entropy. By adopting Leontief's perspective of the production process as a circular flow, we formulate the process as a Markov chain. Then we derive a measure of economic complexity as the average number of bits required to e…
A MARL system improves productivity on a metallurgical pickling line.
problem Improving productivity on a metallurgical pickling line.
method Combines mathematical modeling and Multi-Agent Reinforcement Learning (MARL).
result Significant improvement in automation systems.
Energy consumption for hot water production is a major draw in high efficiency buildings. Optimizing this has typically been approached from a thermodynamics perspective, decoupled from occupant influence. Furthermore, optimization usually presupposes existence of a detailed dynamics model for the hot water system. The…
GenAI adoption paradoxically lowers ROE for U.S. banks, with spillovers but systemic risk concerns.
problem Productivity paradox and implementation costs in U.S. banking sector with AI adoption.
method Dynamic Spatial Durbin Models (DSDM) and Synthetic Difference-in-Differences (SDID) for causal inference.
result AI adoption leads to a 428-basis-point decline in ROE for banks, with spillovers but systemic risk implications.
Study on special symmetries in biwarped product 3-manifolds.
problem Characterizing Killing vector fields on biwarped product-type 3-manifolds.
method Derived system of equations for Killing fields and described their structure.
result Families of solutions found, including explicit examples.
The study develops a logic reasoner to verify MS case management specifications.
problem Ensuring correctness and solvability of abstract clinical work products.
method Developed a logic reasoner using UML class and state diagrams, SPIN, and ODM.
result Formal representations of UML diagrams proved consistent for MS case management.