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Probability

1043 directly classified papers

Papers per year

Papers

A Stein Goodness-of-test for Exponential Random Graph Models AISTATS 2021
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds NIPS 2021
Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions NIPS 2021
Concentration inequalities under sub-Gaussian and sub-exponential conditions NIPS 2021
Symbol Grounding and Task Learning from Imperfect Corrections ACL 2021
On Solving Probabilistic Linear Diophantine Equations JMLR 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support NIPS 2021
Why Adversarial Interaction Creates Non-Homogeneous Patterns: A Pseudo-Reaction-Diffusion Model for Turing Instability AAAI 2021
Faster and Better Simple Temporal Problems AAAI 2021
A Kernel-based Test of Independence for Cluster-correlated Data NIPS 2021
Compressed Maximum Likelihood ICML 2021
Actively Identifying Causal Effects with Latent Variables Given Only Response Variable Observable NIPS 2021
Analysis of stochastic Lanczos quadrature for spectrum approximation ICML 2021
Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo ICML 2021
Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold ICML 2021
Detection of Signal in the Spiked Rectangular Models ICML 2021
Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy AISTATS 2021
Inference of Black Hole Fluid-Dynamics From Sparse Interferometric Measurements ICCV 2021
The Many Faces of Adversarial Risk NIPS 2021
Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently AAAI 2021
Updating the Belief Promotion Operator IJCAI 2021
Privately Learning Mixtures of Axis-Aligned Gaussians NIPS 2021
Hoeffding's Inequality for General Markov Chains and Its Applications to Statistical Learning JMLR 2021
Consistent estimation of small masses in feature sampling JMLR 2021
Quasi-Monte Carlo Quasi-Newton in Variational Bayes JMLR 2021