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Razvan Marinescu

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#artificial intelligence Preprint Oct 2026

AEGIS: Differentiable Mars Climate Model with Neural Closures

General circulation models (GCMs) are the primary tool for simulating planetary atmospheres. They play a vital role in understanding Mars's atmosphere, as forecasting its unique weather is mission-critical for operations such as entry, descent, and landing. Mars poses unusual challenges for these models, as observation...

Sameera S. Kashyap, Victor Cruz, Á. Yépez et al. · 0 citations

Hessian Matching for Machine-Learned Coarse-Grained Molecular Dynamics

This work introduces a framework that augments force matching with stochastic Hessian-vector product (HVP) matching, instilling second-order curvature information into CG potentials without constructing the full Hessian.

S. Murdeshwar, Sanjit Shashi, Kevin Bachelor et al. · 0 citations
#machine learning Open access Jan 2026

Holographic generative flows with AdS/CFT

This work builds Generative AdS, an approach to generative flow matching in which the dynamics are represented by the evolution of fields in AdS, together with a residual correction learned by a neural network.

Ehsan Mirafzali, Sanjit Shashi, S. Murdeshwar et al. · 0 citations
Preprint Aug 2026

Logarithmic derivatives of variational and singular stochastic partial differential equations

For a stochastic partial differential equation posed on a Gelfand triple and satisfying the fully local monotone conditions of R\"ockner, Shang and Zhang, we compute the logarithmic derivative of the law of the solution at a fixed time along a prescribed direction of the state space. The formula is intrinsic, being exp...

Ehsan Mirafzali, F. Proske, Razvan Marinescu · 0 citations

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