Probability

Sampling from Arbitrary Functions via PSD Models AISTATS 2022 Sampling from Log-Concave Distributions with Infinity-Distance Guarantees NeurIPS 2022 Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes ICML 2022 Segmenting Numerical Substitution Ciphers EMNLP 2022 Signature Moments to Characterize Laws of Stochastic Processes JMLR 2022 Sqrt(d) Dimension Dependence of Langevin Monte Carlo ICLR 2022 Three rates of convergence or separation via U-statistics in a dependent framework JMLR 2022 Trustworthy Monte Carlo NeurIPS 2022 Tuning-Free Generalized Hamiltonian Monte Carlo AISTATS 2022 When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint JMLR 2022 A Central Limit Theorem for Differentially Private Query Answering NeurIPS 2021 Almost sure convergence rates for Stochastic Gradient Descent and Stochastic Heavy Ball COLT 2021 An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo AISTATS 2021 Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler JMLR 2021 A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting ICML 2021 Bayesian Quadrature on Riemannian Data Manifolds ICML 2021 Bounding Causal Effects on Continuous Outcome AAAI 2021 Calibrated Adaptive Probabilistic ODE Solvers AISTATS 2021 Compressed Maximum Likelihood ICML 2021 Consensus-Based Optimization on the Sphere: Convergence to Global Minimizers and Machine Learning JMLR 2021 Couplings for Multinomial Hamiltonian Monte Carlo AISTATS 2021 Detection of Signal in the Spiked Rectangular Models ICML 2021 Diffusion Source Identification on Networks with Statistical Confidence ICML 2021 Efficient Sampling of Dependency Structure EMNLP 2021 Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions NeurIPS 2021