 Metric Flow Matching for Smooth Interpolations on the Data ManifoldNeural Information Processing Systems (NeurIPS), 2024 |
 Riemannian Laplace Approximation with the Fisher MetricInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 |
 Riemannian Laplace approximations for Bayesian neural networksNeural Information Processing Systems (NeurIPS), 2023 |
 Riemannian Metric Learning via Optimal TransportInternational Conference on Learning Representations (ICLR), 2022 |
 Pulling back information geometryInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 |
 Data Augmentation in High Dimensional Low Sample Size Setting Using a
Geometry-Based Variational AutoencoderIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 |
 A prior-based approximate latent Riemannian metricInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 |
 Bayesian Quadrature on Riemannian Data ManifoldsInternational Conference on Machine Learning (ICML), 2021 |
 Geometrically Enriched Latent SpacesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 |
 Variational Autoencoders with Riemannian Brownian Motion PriorsInternational Conference on Machine Learning (ICML), 2020 |
 Improved Pose Graph Optimization for Planar Motions Using Riemannian
Geometry on the Manifold of Dual QuaternionsIFAC-PapersOnLine (IFAC-PapersOnLine), 2019 |
