2 citations · 3 across the 9 of their papers we have counts for
10 papers
T-SNN: Temporal Simplicial Neural Network for EEG Decoding
Nikita Malik, Shubhajit Roy, Mohit Kataria +4
Decoding brain states requires models that capture both the evolution of neural activity and interactions among groups of brain regions. Existing EEG methods often treat recordings…
Density-Robust Spherical Coordinates from Persistent Cohomology
Nick Nordwald, Inés García-Redondo, Anthea Monod
Persistent cohomology provides a principled framework for constructing nonlinear coordinates that reflect the topology of data. However, these topological coordinates can be severe…
Topological Signatures of Grokking
Yifan Tang, Qiquan Wang, Inés García-Redondo +1
We study the grokking phenomenon through the lens of topology. Using persistent homology on point clouds derived from the embedding matrices of a range of models trained on modular…
Effective Resistance in Simplicial Complexes as Bilinear Forms: Generalizations and Properties
Inés García-Redondo, Claudia Landi, Sarah Percival +3
The concept of effective resistance, originally introduced in electrical circuit theory, has been extended to the setting of graphs by interpreting each edge as a resistor. In this…
Finding the Cores of Higher Graphs Using Geometric and Topological Means: A Survey
Inés García-Redondo, Claudia Landi, Sarah Percival +3
In this survey, we explore recent literature on finding the cores of higher graphs using geometric and topological means. We study graphs, hypergraphs, and simplicial complexes, al…
The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology
Aideen Fay, Inés García-Redondo, Qiquan Wang +2
Existing interpretability methods for Large Language Models (LLMs) predominantly capture linear directions or isolated features. This overlooks the high-dimensional, relational, an…
Confidence Bands for Multiparameter Persistence Landscapes
Inés García-Redondo, Anthea Monod, Qiquan Wang
Multiparameter persistent homology is a generalization of classical persistent homology, a central and widely-used methodology from topological data analysis, which takes into acco…
On the Limitations of Fractal Dimension as a Measure of Generalization
Charlie B. Tan, Inés García-Redondo, Qiquan Wang +2
Bounding and predicting the generalization gap of overparameterized neural networks remains a central open problem in theoretical machine learning. There is a recent and growing bo…
Stability for Inference with Persistent Homology Rank Functions
Qiquan Wang, Inés García-Redondo, Pierre Faugère +2
Persistent homology barcodes and diagrams are a cornerstone of topological data analysis that capture the "shape" of a wide range of complex data structures, such as point clouds,…
Fast Topological Signal Identification and Persistent Cohomological Cycle Matching
Inés García-Redondo, Anthea Monod, Anna Song
Within the context of topological data analysis, the problems of identifying topological significance and matching signals across datasets are important and useful inferential task…