Stars
CLI tool for sandboxing the pi coding agent in per-project Lima VMs on macOS ARM. Each project gets an isolated Ubuntu VM with pi pre-installed, host files mounted in, and environment-specific conf…
Run tested, autonomous agent workflows on your data for meaningful decision-making
Contains the code accompanying the paper "Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation".
Python Package which collects simulators for Sequential Sampling Models
A python package for learning prior distributions based on expert knowledge
Effector - a Python package for global and regional effect methods
This is a community-driven collection of resources around amortized inference.
Learning Robust Statistics for Simulation-Based Inference Under Model Misspecification (Huang et al., Neurips 2023)
Domain adaptation made easy. Fully featured, modular, and customizable.
A collection of AWESOME things about domain adaptation
Deep Learning project template best practices with Pytorch Lightning, Hydra, Tensorboard.
Database with posteriors of interest for Bayesian inference
PriorDB aims to make choosing a prior for a Bayesian model easier
Method for translating expert knowledge into corresponding prior distributions for parameters in a Bayesian model.
Contains the code accompanying the paper "Sensitivity-Aware Amortized Bayesian Inference".
Open-source framework for uncertainty and deep learning models in PyTorch 🌱
Helping you manage your data science projects sanely.
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Python package to accelerate research on generalized out-of-distribution (OOD) detection.
High-performance vector similarity library in Rust with Python bindings: Spearman, Kendall, distance correlation, Jensen-Shannon, Hoeffding's D, and bootstrapped confidence intervals
Community-sourced list of papers and resources on neural simulation-based inference.
Repository for fitting Drift-Diffusion models with identifiable within-trial noise parameters in Python using BayesFlow
Out-of-distribution detection, robustness, and generalization resources. The repository contains a curated list of papers, tutorials, books, videos, articles and open-source libraries etc
A simple implimentation of Bayesian Flow Networks (BFN)
A collection of (mostly) technical things every software developer should know about
Contains the code for reproducing the experiments and results of the paper "Neural Superstatistics: A Bayesian Method for Estimating Dynamic Models of Cognition".
Contains the code accompanying the paper "JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models"
Code accompanying the paper "A Deep Learning Method for Comparing Bayesian Hierarchical Models".