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.
Paper predicts international trade flows using machine learning and factorization models.
Proposes a Coulomb-like model for international trade flows, fitting real-world data.
Method determines latent dimensionality in international trade flows.
Let S be a closed, connected, orientable surface of genus at least 2, and let C(S) denote the deformation space of convex real projective structures S. In this article, we introduce two new flows on C(S), which we call the internal bulging flow and the eruption flow. These are geometrically defined flows associated to …
Based on the approach of flow distances, the international trade flow system is studied from the perspective of multi-layer flow network. A model of multi-layer flow network is proposed for modelling and analyzing multiple types of flows in flow systems. Then, flow distances are introduced, and symmetric minimum flow d…
Paper extends port-Hamiltonian model to include internal energy for compressible and incompressible flow.
Study uses Google matrix analysis to show how COVID-19 changed international trade flows.
Modeling influenza spread using feature engineering and international flow deconvolution.
This paper investigates whether the gravity model (GM) can explain the statistical properties of the International Trade Network (ITN). We fit data on international-trade flows with a GM specification using alternative fitting techniques and we employ GM estimates to build a weighted predicted ITN, whose topological pr…
Bayesian hierarchical tensor factorization model for international trade flows
These lecture notes give an introduction to the Kahler-Ricci flow. They are based on lectures given by the authors at the conference "Analytic Aspects of Complex Algebraic Geometry", held at the Centre International de Rencontres Mathematiques in Luminy, in February 2011.
Vector fields on schemes have flows if rings are finitely generated.
In work the internal structure of de Rham cohomology is considered. As examples the phase flows in admitting the Nambu Poisson structure are studied.
Investigates optimal strategies for market makers using internal liquidity.
In this paper, we present a new approach to interpret deep learning models. By coupling mutual information with network science, we explore how information flows through feedforward networks. We show that efficiently approximating mutual information allows us to create an information measure that quantifies how much in…
We propose a unified modelling framework that theoretically justifies the main empirical regularities characterizing the international trade network. Each country is associated to a Polya urn whose composition controls the propensity of the country to trade with other countries. The urn composition is updated through t…
Autoregressive models are among the best performing neural density estimators. We describe an approach for increasing the flexibility of an autoregressive model, based on modelling the random numbers that the model uses internally when generating data. By constructing a stack of autoregressive models, each modelling th…
Current machine learning techniques proposed to automatically discover a robot kinematics usually rely on a priori information about the robot's structure, sensors properties or end-effector position. This paper proposes a method to estimate a certain aspect of the forward kinematics model with no such information. An …
New model estimates Gibbs free energies using machine learning and isobaric-isothermal flows.
Study controls bifurcations in Eulerian flows with multiple Hopf singularities.
This article is a continuation of earlier work [R.L. Huang and Y.H. Ye, On the second boundary value problem for a class of fully nonlinear flows I, to appear in International Mathematics Research Notices], where the long time existence and convergence were given on some general parabolic type special Lagrangian equati…
Armed conflict has led to an unprecedented number of internally displaced persons (IDPs) - individuals who are forced out of their homes but remain within their country. IDPs often urgently require shelter, food, and healthcare, yet prediction of when large fluxes of IDPs will cross into an area remains a major challen…
The paper studies scaling limits of Wasserstein metrics on Gaussian mixture models.
This paper offers a framework for FX dealers to decide between internalizing and externalizing their market making to balance risk control and costs.
Clarifies interest rate cap rules for loans with unconventional cash flows.
This work presents MeKDDaM-SAGA, computer-aided automation software for implementing a novel knowledge discovery and data mining process model that was designed for performing justifiable, traceable and reproducible metabolomics data analysis. The process model focuses on achieving metabolomics analytical objectives an…
New moving average adapts weight dynamically based on polynomial and wavefunction.
International trade fluxes evolve as countries revise their portfolios of trade products towards economic development. Accordingly products' shares in international trade vary with time, reflecting the transfer of capital between distinct industrial sectors. Here we analyze the share of hundreds of product categories i…
Deep neural networks (DNNs) are shown to be promising solutions in many challenging artificial intelligence tasks. However, it is very hard to figure out whether the low precision of a DNN model is an inevitable result, or caused by defects. This paper aims at addressing this challenging problem. We find that the inter…
Study uses Perelman and Ricci flow methods to analyze economic inequality.
Study optimal strategies for unwinding uncertain order flows in financial trading desks.
This paper begins to explore the determinants of the topological properties of the international - trade network (ITN). We fit bilateral-trade flows using a standard gravity equation to build a "residual" ITN where trade-link weights are depurated from geographical distance, size, border effects, trade agreements, and …
Achieving international food security requires improved understanding of how international trade networks connect countries around the world through the import-export flows of food commodities. The properties of food trade networks are still poorly documented, especially from a multi-network perspective. In particular,…
We analyse a multiplex of networks between OECD countries during the decade 2002-2010, which consists of five financial layers, given by foreign direct investment, equity securities, short-term, long-term and total debt securities, and five environmental layers, given by emissions of N O x, P M 10 SO 2, CO 2 equivalent…
Smooth flows for physical systems with smooth energies and forces.
New method maps global value chains at product level from trade data.
Infinite volume found in the thick part of -Hitchin-Riemann moduli space.
A new training method for efficient Boltzmann generators.
New normalizing flows model molecular crystal structures.
It is common wisdom that no nation is an isolated economic island. All nations participate in the global economy and are linked together through trade and finance. Here we analyze international trade network (ITN), being the network of import-export relationships between countries. We show that in each year over the an…
Brazil proposes a new BRICS trade currency to dominate international trade.
Internal Lagrangians derived from variational principles.
In this note we study the bilateral merchandise trade flows between 186 countries over the 1948-2005 period using data from the International Monetary Fund. We use Pajek to identify network structure and behavior across thresholds and over time. In particular, we focus on the evolution of trade "islands" in the a world…
Model predicts internal fraud in retail banking is cyclical and influenced by corruption.
The predictive power of neural networks often costs model interpretability. Several techniques have been developed for explaining model outputs in terms of input features; however, it is difficult to translate such interpretations into actionable insight. Here, we propose a framework to analyze predictions in terms of …
The paper proposes a new algorithm for dealer markets that incorporates hedging and market impact.
Jan Tinbergen, the first recipient of the Nobel Memorial Prize in Economics in 1969, obtained his PhD in physics at the University of Leiden under the supervision of Paul Ehrenfest in 1929. Among many achievements as an economist after his training as a physicist, Tinbergen proposed the so-called Gravity Model of inter…
We study the moduli space of SU(3) structure manifolds X that form the internal compact spaces in four-dimensional N=1/2 domain wall solutions of heterotic supergravity with flux. Together with the direction perpendicular to the four-dimensional domain wall, X forms a non-compact 7-manifold Y with torsionful G2 structu…