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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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4 results for “quasipotential”

Controlling mean exit time of stochastic dynamical systems based on quasipotential and machine learningstat.ML

New method controls mean exit time in stochastic systems using machine learning and quasipotential.

problem Controlling mean exit time in stochastic dynamical systems with white noise.

method Developed a neural network to compute the quasipotential function and designed an algorithm to calculate the controller.

result Effective and accurate control strategy demonstrated through numerical experiments.

stochastic dynamical systems mean exit time quasipotential machine learning white noise

2022-09-27abs ↗pdf ↗

Sparse identification of quasipotentials via a combined data-driven methodmath.DS

Discovering quasipotential equations from data using machine learning.

problem Understanding escape mechanisms from metastable states in nonlinear systems.

method Combining neural networks and sparse regression to symbolically reconstruct quasipotential equations.

result Model-unbiased analytical forms of quasipotential discovered directly from data.

quasipotential machine learning nonlinear dynamics metastability energy landscapes

2024-07-06abs ↗pdf ↗

Computing large deviation prefactors of stochastic dynamical systems based on machine learningstat.ML

The paper uses machine learning to compute rare event probabilities in stochastic systems.

problem Characterizing rare events in stochastic dynamical systems with weak noise.

method Developed a neural network framework for computing quasipotential, most probable paths, and prefactors.

result Demonstrated higher effectiveness and accuracy of the algorithm in calculating mean exit times.

large deviation theory stochastic dynamical systems machine learning prefactors quasipotential

2023-06-20abs ↗pdf ↗

Dynamical Landscape and Multistability of a Climate Modelphysics.ao-ph

Study identifies new stable climate states in climate model.

problem Understanding multistability and transitions in climate models.

method Combination of quasipotential theory and manifold learning.

result Discovery of a third stable climate state not previously known.

climate model multistability quasipotential manifold learning negative feedback

2020-10-20abs ↗pdf ↗