Pinned Repositories
amortized-conditioning-engine
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference (Chang et al., AISTATS 2025)
bads
Bayesian Adaptive Direct Search (BADS) optimization algorithm for model fitting in MATLAB
gpyreg
Lightweight Gaussian process regression package in Python.
ibs
Inverse binomial sampling for efficient log-likelihood estimation of simulator models in MATLAB
normalizing-flow-regression
Normalizing Flow Regression for Bayesian Inference with Offline Likelihood Evaluations
pybads
PyBADS: Bayesian Adaptive Direct Search optimization algorithm for model fitting in Python
pyibs
Inverse binomial sampling for efficient log-likelihood estimation of simulator models in Python
pyvbmc
PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
relational-neural-processes
Practical Equivariances via Relational Conditional Neural Processes (Huang et al., NeurIPS 2023)
vbmc
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
acerbilab's Repositories
acerbilab/bads
Bayesian Adaptive Direct Search (BADS) optimization algorithm for model fitting in MATLAB
acerbilab/vbmc
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
acerbilab/pyvbmc
PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
acerbilab/pybads
PyBADS: Bayesian Adaptive Direct Search optimization algorithm for model fitting in Python
acerbilab/ibs
Inverse binomial sampling for efficient log-likelihood estimation of simulator models in MATLAB
acerbilab/amortized-conditioning-engine
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference (Chang et al., AISTATS 2025)
acerbilab/pyibs
Inverse binomial sampling for efficient log-likelihood estimation of simulator models in Python
acerbilab/gpyreg
Lightweight Gaussian process regression package in Python.
acerbilab/normalizing-flow-regression
Normalizing Flow Regression for Bayesian Inference with Offline Likelihood Evaluations
acerbilab/relational-neural-processes
Practical Equivariances via Relational Conditional Neural Processes (Huang et al., NeurIPS 2023)
acerbilab/pubs-llms
Our publications in an LLM-friendly text-only Markdown format
acerbilab/.github
acerbilab/conda-forge-staged-recipes
Fork for contributing conda-forge recipes (see https://conda-forge.org/docs/maintainer/adding_pkgs.html).
acerbilab/handbook
Lab handbook.
acerbilab/helsinki-probml-pubs
Helsinki ProbML Lab Publications Page Automation
acerbilab/mhi-resources
Useful information for members of the lab.
acerbilab/old-datasets
Datasets of old published papers.
acerbilab/S-VBMC
acerbilab/vsbq