weak convergence

Exploring Novel Uncertainty Quantification through Forward Intensity Function Modeling JMLR 2026 Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity ICML 2024 High Rank Path Development: an approach to learning the filtration of stochastic processes NeurIPS 2024 Targeted Separation and Convergence with Kernel Discrepancies JMLR 2024 The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize NeurIPS 2024 Metrizing Weak Convergence with Maximum Mean Discrepancies JMLR 2023 Large-width functional asymptotics for deep Gaussian neural networks ICLR 2021 Identifiability and Consistent Estimation of Nonparametric Translation Hidden Markov Models with General State Space JMLR 2020 Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance NeurIPS 2019 Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions JMLR 2018 Approximation and Convergence Properties of Generative Adversarial Learning NeurIPS 2017 Measuring Sample Quality with Kernels ICML 2017 Weak Convergence Properties of Constrained Emphatic Temporal-difference Learning with Constant and Slowly Diminishing Stepsize JMLR 2016