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Bayesian Inference

4,821 papers

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Papers

Stochastically Dominant Distributional Reinforcement Learning ICML 2020
On Approximate Thompson Sampling with Langevin Algorithms ICML 2020
Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification ICML 2020
Training Binary Neural Networks using the Bayesian Learning Rule ICML 2020
Projective Preferential Bayesian Optimization ICML 2020
Involutive MCMC: a Unifying Framework ICML 2020
Knowing The What But Not The Where in Bayesian Optimization ICML 2020
Robust Bayesian Classification Using An Optimistic Score Ratio ICML 2020
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation ICML 2020
Implicit Generative Modeling for Efficient Exploration ICML 2020
On Semi-parametric Inference for BART ICML 2020
Double-Loop Unadjusted Langevin Algorithm ICML 2020
Bayesian Optimisation over Multiple Continuous and Categorical Inputs ICML 2020
Inter-domain Deep Gaussian Processes ICML 2020
A Quantile-based Approach for Hyperparameter Transfer Learning ICML 2020
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise ICML 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization ICML 2020
Variational Imitation Learning with Diverse-quality Demonstrations ICML 2020
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances ICML 2020
Bayesian Differential Privacy for Machine Learning ICML 2020
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables ICML 2020
Sequential Cooperative Bayesian Inference ICML 2020
Thompson Sampling via Local Uncertainty ICML 2020
Amortised Learning by Wake-Sleep ICML 2020