Probability

Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations ICML 2022 Bayesian spillover graphs for dynamic networks UAI 2022 Beyond black box densities: Parameter learning for the deviated components NeurIPS 2022 Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets JMLR 2022 Bounds on Causal Effects and Application to High Dimensional Data AAAI 2022 BR-SNIS: Bias Reduced Self-Normalized Importance Sampling NeurIPS 2022 ButterflyFlow: Building Invertible Layers with Butterfly Matrices ICML 2022 Capturing Graphs with Hypo-Elliptic Diffusions NeurIPS 2022 C-MinHash: Improving Minwise Hashing with Circulant Permutation ICML 2022 Community Recovery in the Degree-Heterogeneous Stochastic Block Model COLT 2022 Computing Wasserstein-p Distance Between Images With Linear Cost CVPR 2022 Continuously Tempered PDMP samplers NeurIPS 2022 Convergence Guarantees for the Good-Turing Estimator JMLR 2022 Cycle Consistent Probability Divergences Across Different Spaces AISTATS 2022 Data-Driven Chance Constrained Control using Kernel Distribution Embeddings L4DC 2022 Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown AISTATS 2022 Differential privacy for symmetric log-concave mechanisms AISTATS 2022 Discrete Probabilistic Inverse Optimal Transport ICML 2022 Distributional Convergence of the Sliced Wasserstein Process NeurIPS 2022 Distribution Regression with Sliced Wasserstein Kernels ICML 2022 Dynamic Fair Division with Partial Information NeurIPS 2022 Efficient Aggregated Kernel Tests using Incomplete U-statistics NeurIPS 2022 Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes AISTATS 2022 Efficient Optimal Transport Algorithm by Accelerated Gradient Descent AAAI 2022 Efficient Sampling on Riemannian Manifolds via Langevin MCMC NeurIPS 2022