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cs.LG2026
Operational Abstractions of Neural Network Concepts via Topological Representations
Mathieu Pont, Christoph Garth
Concept-based methods provide a semantic level for interpreting and manipulating learned representations, but existing editing approaches are typically specialized to particular in…
cs.LG2024
A Practical Solver for Scalar Data Topological Simplification
Mohamed Kissi, Mathieu Pont, Joshua A. Levine +1
This paper presents a practical approach for the optimization of topological simplification, a central pre-processing step for the analysis and visualization of scalar data. Given…
cs.LG2023
Wasserstein Auto-Encoders of Merge Trees (and Persistence Diagrams)
Mahieu Pont, Julien Tierny
This paper presents a computational framework for the Wasserstein auto-encoding of merge trees (MT-WAE), a novel extension of the classical auto-encoder neural network architecture…