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From the 1 of 5 linked papers with an AI index.

activity
20242026
collaborators

5 papers

astro-ph.IM2026

Joint Estimation of Properties of the Lunar Subsurface and Galactic Foregrounds with LuSEE-Night

Fatima Yousuf, Zack Li, Stuart D. Bale +36

The paper presents a Bayesian method to simultaneously estimate the dielectric properties of the lunar subsurface at the LuSEE‑Night landing site and the parameters of the galactic…

cs.LG2026

Persistence-Augmented Neural Networks

Elena Xinyi Wang, Arnur Nigmetov, Dmitriy Morozov

Topological Data Analysis (TDA) provides tools to describe the shape of data, but integrating topological features into deep learning pipelines remains challenging, especially when…

cs.LG2026

On Neural Scaling Laws for Weather Emulation through Continual Training

Shashank Subramanian, Alexander Kiefer, Arnur Nigmetov +3

Neural scaling laws, which in some domains can predict the performance of large neural networks as a function of model, data, and compute scale, are the cornerstone of building fou…

cond-mat.soft2025

Topological potentials guiding protein self-assembly

Ivan Spirandelli, Arnur Nigmetov, Dmitriy Morozov +1

The simulated self-assembly of molecular building blocks into functional complexes is a key area of study in computational biology and materials science. Self-assembly simulations…

cs.CG2024

Distributed Computation of Persistent Cohomology

Arnur Nigmetov, Dmitriy Morozov

Persistent (co)homology is a central construction in topological data analysis, where it is used to quantify prominence of features in data to produce stable descriptors suitable f…