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Probabilistic Modeling

2591 directly classified papers

Papers per year

Papers

SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data ICML 2021
Graph Mixture Density Networks ICML 2021
A Game-Theoretic Account of Responsibility Allocation IJCAI 2021
Deconditional Downscaling with Gaussian Processes NIPS 2021
Automatic variational inference with cascading flows ICML 2021
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond NIPS 2021
Abstract Spatial-Temporal Reasoning via Probabilistic Abduction and Execution CVPR 2021
Latent variable modeling with random features AISTATS 2021
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm NIPS 2021
Learning Fast-Inference Bayesian Networks NIPS 2021
Ordinal Historical Dependence in Graphical Event Models with Tree Representations AAAI 2021
Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model AAAI 2021
Bayesian Topic Regression for Causal Inference EMNLP 2021
Linear-Time Probabilistic Solution of Boundary Value Problems NIPS 2021
Dual Parameterization of Sparse Variational Gaussian Processes NIPS 2021
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space NIPS 2021
DeepGEM: Generalized Expectation-Maximization for Blind Inversion NIPS 2021
Backward-Compatible Prediction Updates: A Probabilistic Approach NIPS 2021
An Alternative Probabilistic Interpretation of the Huber Loss CVPR 2021
On the Convex Combination of Determinantal Point Processes ACML 2021
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference NIPS 2021
Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging AAAI 2021
Sinusoidal Flow: A Fast Invertible Autoregressive Flow ACML 2021
Bayesian Inference for Optimal Transport with Stochastic Cost ACML 2021
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions NIPS 2021