nonparametric inference

Decorrelated Variable Importance JMLR 2024 Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood AAAI 2024 Nonparametric Automatic Differentiation Variational Inference with Spline Approximation AISTATS 2024 Nonparametric Inference under B-bits Quantization JMLR 2024 Nonparametric Extensions of Randomized Response for Private Confidence Sets ICML 2023 Doubly Robust Counterfactual Classification NeurIPS 2022 Inference and Sampling for Archimax Copulas NeurIPS 2022 Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach JMLR 2022 Nonparametric Embeddings of Sparse High-Order Interaction Events ICML 2022 Non-parametric Inference Adaptive to Intrinsic Dimension CLeaR 2022 Non-parametric inference of relational dependence UAI 2022 Nonparametric estimation of continuous DPPs with kernel methods NeurIPS 2021 Nonparametric Hamiltonian Monte Carlo ICML 2021 Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference AISTATS 2021 A Flexible Framework for Nonparametric Graphical Modeling that Accommodates Machine Learning ICML 2020 Efficient Inference for Nonparametric Hawkes Processes Using Auxiliary Latent Variables JMLR 2020 Adaptive Sensor Placement for Continuous Spaces ICML 2019 Bayesian Deconditional Kernel Mean Embeddings ICML 2019 Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes NeurIPS 2019 Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation NeurIPS 2019 Sharp Theoretical Analysis for Nonparametric Testing under Random Projection COLT 2019 JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes ICML 2015 Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes ICML 2015 Nonparametric Bayesian inference on multivariate exponential families NeurIPS 2014 Recovering Distributions from Gaussian RKHS Embeddings AISTATS 2014