157 citations · 242 across the 16 of their papers we have counts for
18 papers
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
Shashank Subramanian, Peter Harrington, Kurt Keutzer +4
Pre-trained machine learning (ML) models have shown great performance for a wide range of applications, in particular in natural language processing (NLP) and computer vision (CV).…
Fast Merge Tree Computation via SYCL
Arnur Nigmetov, Dmitriy Morozov
A merge tree is a topological descriptor of a real-valued function. Merge trees are used in visualization and topological data analysis, either directly or as a means to another en…
Topological Optimization with Big Steps
Arnur Nigmetov, Dmitriy Morozov
Using persistent homology to guide optimization has emerged as a novel application of topological data analysis. Existing methods treat persistence calculation as a black box and b…
Output-sensitive Computation of Generalized Persistence Diagrams for 2-filtrations
Dmitriy Morozov, Amit Patel
When persistence diagrams are formalized as the Mobius inversion of the birth-death function, they naturally generalize to the multi-parameter setting and enjoy many of the key pro…
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…
PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction
Nicolas Swenson, Aditi S. Krishnapriyan, Aydin Buluc +2
Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While…