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arXiv research

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.

168,695 papers · 148 categories

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89178267356 · Jun 202019922001200920172026
48 results for evolving systems

Geometrically revisits Dupin cyclidic systems using evolving circles and cyclides.

problem Understanding the geometric properties and evolution of Dupin cyclidic systems.
method Evolving initial circles or Dupin cyclides to generate Lamé families of Dupin cyclidic systems in various space forms.
result Lamé families are parallel surfaces in different space forms.

An artificial stock market is established based on multi-agent . Each agent has a limit memory of the history of stock price, and will choose an action according to his memory and trading strategy. The trading strategy of each agent evolves ceaselessly as a result of self-teaching mechanism. Simulation results exhibit …

2004-06-07abs ↗pdf ↗

Generative models speed up complex system simulations.

problem Accurately forecasting the dynamics of complex systems at reduced cost.
method Generative Learning of Effective Dynamics (G-LED) using auto-regressive attention and Bayesian diffusion models.
result Generative models can accurately forecast complex system dynamics at lower computational cost.

Develops a method to construct entire minimal graphs of odd dimensions.

problem Constructing entire minimal graphs of odd dimensions and arbitrary codimensions.
method Evolving-plane ansatz reducing minimal surface system to geodesic equation on Grassmannian.
result Yields a rich family of explicit entire minimal graphs of odd dimension and arbitrary codimension.

Click-through rate~(CTR) prediction, whose goal is to estimate the probability of the user clicks, has become one of the core tasks in advertising systems. For CTR prediction model, it is necessary to capture the latent user interest behind the user behavior data. Besides, considering the changing of the external envir…

2018-09-11abs ↗pdf ↗

New method clusters evolving networks using spatio-temporal graph Laplacian.

problem Clustering communities in time-varying graphs.
method Extends spectral clustering to dynamic graphs using CCA and spatio-temporal graph Laplacian.
result The spatio-temporal graph Laplacian clearly interprets cluster evolution over time.

Method predicts how probability distributions evolve over time.

problem Predicting how systems described by probability distributions evolve under different conditions.
method Wasserstein Parallel Transport
result Wasserstein Parallel Transport provides counterfactual comparisons of distributional dynamics.

Bayesian optimization of antibodies learns from immune system evolution.

problem Efficiently optimizing antibody sequences in a large space of possibilities.
method Bayesian optimization guided by a generative model of evolving antibody sequences.
result CloneBO optimizes antibodies more efficiently than previous methods.

DISCO predicts system states from short trajectories using an evolved operator.

problem Predicting next states of dynamical systems governed by unknown PDEs.
method DISCO uses a hypernetwork to generate parameters of a smaller operator network for state prediction.
result DISCO achieves state-of-the-art performance with fewer training epochs and generalizes well.

Enhanced fuzzy system predicts chaotic time series with improved accuracy.

problem Forecasting chaotic time series with high uncertainty.
method Combines evolving fuzzy systems, participatory learning, KRLS, and type-2 fuzzy sets.
result Proposed model outperforms other methods in accuracy and complexity.

We show that a simple model of a spatially resolved evolving economic system, which has a steady state under simultaneous updating, shows stable oscillations in price when updated asynchronously. The oscillations arise from a gradual decline of the mean price due to competition among sellers competing for the same reso…

2008-01-25abs ↗pdf ↗

Many networks are complex dynamical systems, where both attributes of nodes and topology of the network (link structure) can change with time. We propose a model of co-evolving networks where both node at- tributes and network structure evolve under mutual influence. Specifically, we consider a mixed membership stochas…

2011-06-14abs ↗pdf ↗

Adaptive optimal control using value iteration (VI) initiated from a stabilizing policy is theoretically analyzed in various aspects including the continuity of the result, the stability of the system operated using any single/constant resulting control policy, the stability of the system operated using the evolving/ti…

2014-12-17abs ↗pdf ↗

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…

2004-02-26abs ↗pdf ↗

Under proportional transaction costs, a price process is said to have a consistent price system, if there is a semimartingale with an equivalent martingale measure that evolves within the bid-ask spread. We show that a continuous, multi-asset price process has a consistent price system, under arbitrarily small proporti…

2013-10-29abs ↗pdf ↗

This work discovers latent field effects governing interacting dynamical systems.

problem Discovering field effects governing interacting dynamical systems.
method Proposes neural fields to learn latent force fields from observed dynamics, disentangling local object interactions and global field effects.
result Accurately discovers latent field effects in various dynamical systems.

A new method simulates large, diverse populations of learning agents evolving in games.

problem Limited scalability and efficiency of Multi-Agent Reinforcement Learning.
method Parallelizable implementation of Policy Gradient and Opponent-Learning Awareness for evolutionary simulations.
result Simulated large, diverse populations of learning agents evolve under various strategies.

We study an agent-based model of evolution of wealth distribution in a macro-economic system. The evolution is driven by multiplicative stochastic fluctuations governed by the law of proportionate growth and interactions between agents. We are mainly interested in interactions increasing wealth inequality that is in a …

2018-02-05abs ↗pdf ↗

Study on evolving interfaces with complex curvature and density effects.

problem Understanding the dynamics of evolving heterogeneous elastic interfaces.
method Modeling an evolving curve with a density function, analyzing the associated gradient flow evolution.
result Analysis of the preservation and asymptotic behavior of geometric properties in the evolving system.

Financial asset markets are sociotechnical systems whose constituent agents are subject to evolutionary pressure as unprofitable agents exit the marketplace and more profitable agents continue to trade assets. Using a population of evolving zero-intelligence agents and a frequent batch auction price-discovery mechanism…

2018-12-13abs ↗pdf ↗

Latent-state environments with long horizons, such as those faced by recommender systems, pose significant challenges for reinforcement learning (RL). In this work, we identify and analyze several key hurdles for RL in such environments, including belief state error and small action advantage. We develop a general prin…

2019-05-29abs ↗pdf ↗

Financial markets have been extensively studied as highly complex evolving systems. In this paper, we quantify financial price fluctuations through a coupled dynamical system composed of phase oscillators. We find a Financial Coherence and Incoherence (FCI) coexistence collective behavior emerges as the system evolves …

2016-05-08abs ↗pdf ↗

Paper compares five surface Navier-Stokes derivations and finds some are equivalent.

problem Modeling evolving fluidic surfaces using different principles and coordinate systems.
method Systematic comparison of five derivations using tangential and normal components.
result All derivations yield the same tangential surface Navier-Stokes equations.

Develops a neural framework for probabilistic forecasting of dynamical systems.

problem Uncertainty quantification in dynamical systems using trajectory-oriented approaches.
method D2D neural probabilistic forecasting framework using kernel mean embeddings and mixture density networks.
result The D2D model captures distributional evolution in chaotic systems and produces skillful probabilistic forecasts.

In this paper, based on theories of complex adaptive systems, I argue that the main case for antitrust policy should be extended to include the criteria of "evolvability." To date, the main case focuses on economizing, including market power as a key filter for identifying suspect cases. Both production and transaction…

2012-03-06abs ↗pdf ↗

The comparison principle for scalar second order parabolic PDEs on functions u(t,x)u(t,x) admits a topological interpretation: pairs of solutions, u1(t,)u^1(t,\cdot) and u2(t,)u^2(t,\cdot), evolve so as to not increase the intersection number of their graphs. We generalize to the case of multiple solutions $\{u^α(t,\cdot)\}_{α=1}^…

2004-03-18abs ↗pdf ↗

MadEvolve optimizes trading algorithms using LLMs, achieving significant improvements in feature generation and trading strategy optimization.

problem Optimizing trading algorithms for better performance and feature generation.
method A framework inspired by Alpha-Evolve, using LLMs to evolve trading strategies and feature pipelines.
result Significant improvements in trading performance across various tasks, including feature generation and trading strategy optimization.

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 …

2019-07-24abs ↗pdf ↗

The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, there has not been a full investigation of evolving world economic networks with Markov chain formalism. Using the…

2016-11-26abs ↗pdf ↗

We define a large class of integrable nonlinear PDE's, \emph{kk-symmetric AKS systems}, whose solutions evolve on finite dimensional subalgebras of loop algebras, and linearize on an associated algebraic curve. We prove that periodicity of the associated algebraic data implies a type of quasiperiodicity for the soluti…

2006-04-11abs ↗pdf ↗

In classical contagion models, default systems are Markovian conditionally on the observation of their stochastic environment, with interacting intensities. This necessitates that the environment evolves autonomously and is not influenced by the history of the default events. We extend the classical literature and allo…

2017-09-26abs ↗pdf ↗