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Probability

1043 directly classified papers

Papers per year

Papers

Random Matrix Improved Covariance Estimation for a Large Class of Metrics ICML 2019
On two ways to use determinantal point processes for Monte Carlo integration NIPS 2019
Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond NIPS 2019
Online Infix Probability Computation for Probabilistic Finite Automata ACL 2019
High Flux Passive Imaging With Single-Photon Sensors CVPR 2019
Tree-Sliced Variants of Wasserstein Distances NIPS 2019
Practical and Consistent Estimation of f-Divergences NIPS 2019
Determinantal Point Processes for Coresets JMLR 2019
Space and Time Efficient Kernel Density Estimation in High Dimensions NIPS 2019
Estimating Convergence of Markov chains with L-Lag Couplings NIPS 2019
Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights NIPS 2019
Approximate Profile Maximum Likelihood JMLR 2019
Multiplicative local linear hazard estimation and best one-sided cross-validation JMLR 2019
A Representer Theorem for Deep Kernel Learning JMLR 2019
Flexible Modeling of Diversity with Strongly Log-Concave Distributions NIPS 2019
Linear-Complexity Data-Parallel Earth Mover’s Distance Approximations ICML 2019
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior ICML 2019
A Polynomial Time MCMC Method for Sampling from Continuous Determinantal Point Processes ICML 2019
Replica Conditional Sequential Monte Carlo ICML 2019
Accelerated Flow for Probability Distributions ICML 2019
Learning Hawkes Processes Under Synchronization Noise ICML 2019
On the Complexity of Approximating Wasserstein Barycenters ICML 2019
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement ICML 2019
Stochastic Deep Networks ICML 2019
DPPy: DPP Sampling with Python JMLR 2019