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Tag: differential

  • Stochastic Differential Equations and Temperature — NASA Climate Data pt. 2

    Stochastic Differential Equations and Temperature — NASA Climate Data pt. 2 The Ornstein-Uhlenbeck process in Python The post Stochastic Differential Equations and Temperature — NASA Climate Data pt. 2 appeared first on Towards Data Science. Marco Hening Tallarico Go to original source

  • Rao Differential Privacy

    Rao Differential Privacy arXiv:2508.17135v1 Announce Type: new Abstract: Differential privacy (DP) has recently emerged as a definition of privacy to release private estimates. DP calibrates noise to be on the order of an individuals contribution. Due to the this calibration a private estimate obscures any individual while preserving the utility of the estimate. Since the…

  • Differential Privacy in Kernelized Contextual Bandits via Random Projections

    Differential Privacy in Kernelized Contextual Bandits via Random Projections arXiv:2507.13639v1 Announce Type: new Abstract: We consider the problem of contextual kernel bandits with stochastic contexts, where the underlying reward function belongs to a known Reproducing Kernel Hilbert Space. We study this problem under an additional constraint of Differential Privacy, where the agent needs to ensure…

  • A generative modeling / Physics-Informed Neural Network approach to random differential equations

    A generative modeling / Physics-Informed Neural Network approach to random differential equations arXiv:2507.01687v1 Announce Type: new Abstract: The integration of Scientific Machine Learning (SciML) techniques with uncertainty quantification (UQ) represents a rapidly evolving frontier in computational science. This work advances Physics-Informed Neural Networks (PINNs) by incorporating probabilistic frameworks to effectively model uncertainty in complex systems.…

  • When Physics Meets Finance: Using AI to Solve Black-Scholes

    When Physics Meets Finance: Using AI to Solve Black-Scholes DISCLAIMER: This is not financial advice. I’m a PhD in Aerospace Engineering with a strong focus on Machine Learning: I’m not a financial advisor. This article is intended solely to demonstrate the power of Physics-Informed Neural Networks (PINNs) in a financial context. When I was 16,…