10 citations · 21 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
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…
Robustifying State-space Models for Long Sequences via Approximate Diagonalization
Annan Yu, Arnur Nigmetov, Dmitriy Morozov +2
State-space models (SSMs) have recently emerged as a framework for learning long-range sequence tasks. An example is the structured state-space sequence (S4) layer, which uses the…
Topological Regularization via Persistence-Sensitive Optimization
Arnur Nigmetov, Aditi S. Krishnapriyan, Nicole Sanderson +1
Optimization, a key tool in machine learning and statistics, relies on regularization to reduce overfitting. Traditional regularization methods control a norm of the solution to en…