variational optimization

Dual Graph Regularized Deep Unfolding Network for Guided Depth Map Super-resolution CVPR 2026 SSTODE: Ocean-Atmosphere Physics-Informed Neural ODEs for Sea Surface Temperature Prediction AAAI 2026 Geometric Gait Optimization for Kinodynamic Systems Using a Lie Group Integrator RSS 2025 On Probabilistic Embeddings in Optimal Dimension Reduction JMLR 2025 Variational Adversarial Training Towards Policies with Improved Robustness AISTATS 2025 A Fair Generative Model Using LeCam Divergence AAAI 2023 VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning NeurIPS 2023 Efficient Model-Driven Network for Shadow Removal AAAI 2022 Deep Mutual Information Maximin for Cross-Modal Clustering AAAI 2021 Bayesian Pseudocoresets NeurIPS 2020 Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue Problems AISTATS 2020 Information Theoretic lower bounds on negative log likelihood ICLR 2019 Lifting Vectorial Variational Problems: A Natural Formulation Based on Geometric Measure Theory and Discrete Exterior Calculus CVPR 2019 Variational Optimization Based Reinforcement Learning for Infinite Dimensional Stochastic Systems CoRL 2019 Robust Energy Minimization for BRDF-Invariant Shape From Light Fields CVPR 2017 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 Exploiting Spectral-Spatial Correlation for Coded Hyperspectral Image Restoration CVPR 2016 Intrinsic Scene Decomposition From RGB-D images ICCV 2015 Variational PatchMatch MultiView Reconstruction and Refinement ICCV 2015 Nonnegative dictionary learning in the exponential noise model for adaptive music signal representation NeurIPS 2011