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06/27/2023
PyBADS: Fast and robust black-box optimization in Python
PyBADS is a Python implementation of the Bayesian Adaptive Direct Search...
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06/19/2023
Practical Equivariances via Relational Conditional Neural Processes
Conditional Neural Processes (CNPs) are a class of metalearning models p...
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06/05/2023
Input gradient diversity for neural network ensembles
Deep Ensembles (DEs) demonstrate improved accuracy, calibration and robu...
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05/25/2023
Learning Robust Statistics for Simulation-based Inference under Model Misspecification
Simulation-based inference (SBI) methods such as approximate Bayesian co...
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03/16/2023
PyVBMC: Efficient Bayesian inference in Python
PyVBMC is a Python implementation of the Variational Bayesian Monte Carl...
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03/09/2023
Fast post-process Bayesian inference with Sparse Variational Bayesian Monte Carlo
We introduce Sparse Variational Bayesian Monte Carlo (SVBMC), a method f...
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03/03/2023
Online simulator-based experimental design for cognitive model selection
The problem of model selection with a limited number of experimental tri...
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06/06/2022
Tackling covariate shift with node-based Bayesian neural networks
Bayesian neural networks (BNNs) promise improved generalization under co...
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02/22/2022
Parallel MCMC Without Embarrassing Failures
Embarrassingly parallel Markov Chain Monte Carlo (MCMC) exploits paralle...
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06/15/2020
Variational Bayesian Monte Carlo with Noisy Likelihoods
Variational Bayesian Monte Carlo (VBMC) is a recently introduced framewo...
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01/12/2020
Unbiased and Efficient Log-Likelihood Estimation with Inverse Binomial Sampling
The fate of scientific hypotheses often relies on the ability of a compu...
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10/12/2018
Variational Bayesian Monte Carlo
Many probabilistic models of interest in scientific computing and machin...
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05/11/2017
