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Bayesian Inference

5,566 papers

Papers per year

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Papers

Active Bayesian Causal Inference NIPS 2022
Fast Instrument Learning with Faster Rates NIPS 2022
Sparse Gaussian Process Hyperparameters: Optimize or Integrate? NIPS 2022
Robust Bayesian Regression via Hard Thresholding NIPS 2022
Variational Model Perturbation for Source-Free Domain Adaptation NIPS 2022
Adjoint-aided inference of Gaussian process driven differential equations NIPS 2022
Bayesian Risk Markov Decision Processes NIPS 2022
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model NIPS 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification NIPS 2022
Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters NIPS 2022
Modeling the Machine Learning Multiverse NIPS 2022
Private Estimation with Public Data NIPS 2022
Reconstruction on Trees and Low-Degree Polynomials NIPS 2022
Pareto Set Learning for Expensive Multi-Objective Optimization NIPS 2022
Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers NIPS 2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation NIPS 2022
Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game NIPS 2022
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction NIPS 2022
Constrained Langevin Algorithms with L-mixing External Random Variables NIPS 2022
Self-Aware Personalized Federated Learning NIPS 2022
Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data NIPS 2022
Bayesian inference via sparse Hamiltonian flows NIPS 2022
Fixed-Distance Hamiltonian Monte Carlo NIPS 2022
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs NIPS 2022
Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks NIPS 2022