data manifold

GeodesicNVS: Probability Density Geodesic Flow Matching for Novel View Synthesis CVPR 2026 A Unified Data Representation Learning for Non-parametric Two-sample Testing UAI 2025 Curvature Enhanced Data Augmentation for Regression ICML 2025 Blind Image Restoration via Fast Diffusion Inversion NeurIPS 2024 Geometry-Aware Instrumental Variable Regression ICML 2024 Lifting Architectural Constraints of Injective Flows ICLR 2024 Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution ICML 2024 Metric Flow Matching for Smooth Interpolations on the Data Manifold NeurIPS 2024 Feasible Recourse Plan via Diverse Interpolation AISTATS 2023 Manifold Restricted Interventional Shapley Values AISTATS 2023 Nearest Neighbor Guidance for Out-of-Distribution Detection ICCV 2023 On Data Manifolds Entailed by Structural Causal Models ICML 2023 Effects of Data Geometry in Early Deep Learning NeurIPS 2022 Generating High Fidelity Data From Low-Density Regions Using Diffusion Models CVPR 2022 MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining ICLR 2022 Scaling Laws from the Data Manifold Dimension JMLR 2022 Score-Based Generative Models Detect Manifolds NeurIPS 2022 Getting a CLUE: A Method for Explaining Uncertainty Estimates ICLR 2021 Improving Transferability of Adversarial Patches on Face Recognition With Generative Models CVPR 2021 Instance-Conditioned GAN NeurIPS 2021 Shapley explainability on the data manifold ICLR 2021 Ensembles of Locally Independent Prediction Models AAAI 2020 Instance Selection for GANs NeurIPS 2020 Learning from Label Proportions with Consistency Regularization ACML 2020 The Shape of Data: Intrinsic Distance for Data Distributions ICLR 2020