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LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models.

, , , , , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 148-157. PMLR, (2019)

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Disentangling Disentanglement., , , and . CoRR, (2018)Rethinking Variational Inference for Probabilistic Programs with Stochastic Support., , and . CoRR, (2023)Certifiably Robust Variational Autoencoders., , , and . CoRR, (2021)Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support., , and . CoRR, (2023)Amortized Rejection Sampling in Universal Probabilistic Programming., , , , , , , , , and 2 other author(s). CoRR, (2019)Trans-Dimensional Generative Modeling via Jump Diffusion Models., , , , , and . CoRR, (2023)Faithful Inversion of Generative Models for Effective Amortized Inference., , , , , , and . NeurIPS, page 3074-3084. (2018)Amortized Rejection Sampling in Universal Probabilistic Programming., , , , , , , , , and 2 other author(s). AISTATS, volume 151 of Proceedings of Machine Learning Research, page 8392-8412. PMLR, (2022)Active Testing: Sample-Efficient Model Evaluation., , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 5753-5763. PMLR, (2021)Tighter Variational Bounds are Not Necessarily Better., , , , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 4274-4282. PMLR, (2018)