maximum mean discrepancy

Understanding the Variance Collapse of SVGD in High Dimensions ICLR 2022 VarScene: A Deep Generative Model for Realistic Scene Graph Synthesis ICML 2022 Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaptation IJCAI 2021 Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression ICML 2021 Deterministic Mini-batch Sequencing for Training Deep Neural Networks AAAI 2021 Distributional Reinforcement Learning for Multi-Dimensional Reward Functions NeurIPS 2021 Distributional Reinforcement Learning via Moment Matching AAAI 2021 Efficient Statistical Tests: A Neural Tangent Kernel Approach ICML 2021 Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing AAAI 2021 Geometric rates of convergence for kernel-based sampling algorithms UAI 2021 Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes NeurIPS 2021 KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support NeurIPS 2021 Kernel Thinning COLT 2021 Maximum Mean Discrepancy Test is Aware of Adversarial Attacks ICML 2021 Neural Tangent Kernel Maximum Mean Discrepancy NeurIPS 2021 Oblivious Data for Fairness with Kernels JMLR 2021 Optimal Bounds between f-Divergences and Integral Probability Metrics JMLR 2021 Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy AISTATS 2021 Predicting With Confidence on Unseen Distributions ICCV 2021 Understanding and Simplifying Perceptual Distances CVPR 2021 A Characteristic Function Approach to Deep Implicit Generative Modeling CVPR 2020 Calibrated Reliable Regression using Maximum Mean Discrepancy NeurIPS 2020 Cross-Domain Adaptation with Discrepancy Minimization for Text-Independent Forensic Speaker Verification Interspeech 2020 Distributionally Robust Bayesian Optimization AISTATS 2020 Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning NeurIPS 2020