27 citations · 31 across the 7 of their papers we have counts for
10 papers
HalluZig: Hallucination Detection using Zigzag Persistence
Shreyas N. Samaga, Gilberto Gonzalez Arroyo, Tamal K. Dey
The factual reliability of Large Language Models (LLMs) remains a critical barrier to their adoption in high-stakes domains due to their propensity to hallucinate. Current detectio…
Quasi Zigzag Persistence: A Topological Framework for Analyzing Time-Varying Data
Tamal K. Dey, Shreyas N. Samaga
In this paper, we propose Quasi Zigzag Persistent Homology (QZPH) as a framework for analyzing time-varying data by integrating multiparameter persistence and zigzag persistence. T…
D-GRIL: End-to-End Topological Learning with 2-parameter Persistence
Soham Mukherjee, Shreyas N. Samaga, Cheng Xin +2
End-to-end topological learning using 1-parameter persistence is well-known. We show that the framework can be enhanced using 2-parameter persistence by adopting a recently introdu…
Efficient Algorithms for Complexes of Persistence Modules with Applications
Tamal K. Dey, Florian Russold, Shreyas N. Samaga
We extend the persistence algorithm, viewed as an algorithm computing the homology of a complex of free persistence or graded modules, to complexes of modules that are not free. We…
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains
Mustafa Hajij, Mathilde Papillon, Florian Frantzen +40
We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: h…
ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Mustafa Hajij, Helen Jenne +53
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competi…
GRIL: A -parameter Persistence Based Vectorization for Machine Learning
Cheng Xin, Soham Mukherjee, Shreyas N. Samaga +1
-parameter persistent homology, a cornerstone in Topological Data Analysis (TDA), studies the evolution of topological features such as connected components and cycles hidden in…
Topological Deep Learning: Going Beyond Graph Data
Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou +11
Topological deep learning is a rapidly growing field that pertains to the development of deep learning models for data supported on topological domains such as simplicial complexes…
Challenges in the application of a mortality prediction model for COVID-19 patients on an Indian cohort
Yukti Makhija, Samarth Bhatia, Shalendra Singh +9
Many countries are now experiencing the third wave of the COVID-19 pandemic straining the healthcare resources with an acute shortage of hospital beds and ventilators for the criti…
On the homotopy type of choice spaces
Shreyas Samaga
We study continuous, symmetric and unanimous aggregation functions and continuous majority functions and prove that such functions exist on a choice space if and only if the choice…