A Python library for amortized Bayesian workflows using generative neural networks.
Amortized Inference for Causal Structure Learning, NeurIPS 2022
This is a community-driven collection of resources around amortized inference.
AISTATS 2019: Reference-based Adversarial Sampling & Its applications to Soft Q-learning
Synthetic Quantum Electrodynamics via Generative AI @ AIMS, Cape Town, May 2025
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition (Huang et al., NeurIPS 2025)
A deep learning framework for structured Bayesian decomposition of sinusoidal mixtures using slot-based conditional flows.
Implementing Bayesian neural networks to close the amortization gap in VAEs in PyTorch
A tutorial on the various methods for performing approximate inference in Bayesian statistics
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