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Disambiguation of "Rainforth, Tom"

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Amortized Rejection Sampling in Universal Probabilistic Programming.

, , , , , , , , , , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 8392-8412. PMLR, (2022)

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To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Tom Hanika University of Kassel

What is the $intrinsic$ dimension of your binary data? -- and how to compute it quickly, and . (2024)

Marieta Ioana Toma

Zentrosomenmorphologie in Prostatakarzinomen: eine immunhistologische Studie mit Korrelation zu DNA-Ploidie und kliniko-pathologischen Parametern. TU Dresden, (2008)

Tom Smolinka

Tom Herrmann

Tom Nilges

 

Other publications of authors with the same name

Disentangling Disentanglement., , , and . CoRR, (2018)Trans-Dimensional Generative Modeling via Jump Diffusion Models., , , , , and . CoRR, (2023)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)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)Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support., , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 829-837. PMLR, (2024)