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Théo Lacombe

2 accepted papers

2024

Diffeomorphic interpolation for efficient persistence-based topological optimization

NeurIPS 2024poster

Topological Data Analysis (TDA) provides a pipeline to extract quantitative and powerful topological descriptors from structured objects. This enables the definition of topological loss functions, which assert to which extent a given object exhibits some topological properties. One can then use th…

Cited by 4SourcePDFScholar
2021

Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs

IJCAI 2021poster

Although neural networks are capable of reaching astonishing performance on a wide variety of contexts, properly training networks on complicated tasks requires expertise and can be expensive from a computational perspective. In industrial applications, data coming from an open-world setting might w…

Cited by 28SourcePDFScholar