function space

Autoencoders in Function Space JMLR 2025 Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space ICLR 2025 Continuum Attention for Neural Operators JMLR 2025 Geometry of Lightning Self-Attention: Identifiability and Dimension ICLR 2025 Mesh Watermark Removal Attack and Mitigation: A Novel Perspective of Function Space AAAI 2025 MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures ICLR 2025 Score-Based Diffusion Models in Function Space JMLR 2025 ∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States ICLR 2024 Consistency of Dictionary-Based Manifold Learning AISTATS 2024 Functional Flow Matching AISTATS 2024 Infinite-Dimensional Diffusion Models JMLR 2024 Learning the Target Network in Function Space ICML 2024 Neural Feature Learning in Function Space JMLR 2024 Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space JMLR 2024 Stochastic Optimal Control for Diffusion Bridges in Function Spaces NeurIPS 2024 Diffusion Generative Models in Infinite Dimensions AISTATS 2023 Function Space Bayesian Pseudocoreset for Bayesian Neural Networks NeurIPS 2023 How do Minimum-Norm Shallow Denoisers Look in Function Space? NeurIPS 2023 HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork ICLR 2023 Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks JMLR 2023 Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion ICML 2023 Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs JMLR 2023 Neural Processes with Stability NeurIPS 2023 Integral Autoencoder Network for Discretization-Invariant Learning JMLR 2022 NOMAD: Nonlinear Manifold Decoders for Operator Learning NeurIPS 2022