probabilistic programming

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1. 1▶5SSD0 - 14 Jan 2022 - Intelligent Agents and Active Inference5SSD0 - 2021Notes
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2. 2▶5SSD0 - 12 Jan 2022 - Dynamic Models5SSD0 - 2021Notes
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3. 3▶5SSD0 - 10 Jan 2022 - Probabilistic Programming 35SSD0 - 2021Notes
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4. 4▶5SSD0 - 22 Dec 2021 - Latent variable models and variational Bayes5SSD0 - 2021Notes
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5. 5▶5SSD0 - 17 Dec 2021 - Bayesian Classification5SSD0 - 2021Notes
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6. 6▶5SSD0 - 15 Dec 2021 - Regression5SSD0 - 2021Notes
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7. 7▶5SSD0 - 15 Dec 2021 - Catch up B1-B75SSD0 - 2021Notes
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8. 8▶5SSD0 - 10 Dec 2021 - Probabilistic Programming 25SSD0 - 2021Notes
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9. 9▶5SSD0 - 8 Dec 2021 - Discrete Data and the Multinomial Distribution5SSD0 - 2021Notes
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10. 10▶5SSD0 - 3 Dec 2021 - Continuous data & the Gaussian Distribution5SSD0 - 2021Notes
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11. 11▶BDA course 2 extra: likelihood, normalization, density, model MBayesian Data AnalysisNotes
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12. 12▶BDA 2019 Lecture 7.2 exchangeabilityBayesian Data AnalysisNotes
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13. 13▶BDA 2019 Lecture 7.1 hierarchical modelsBayesian Data AnalysisNotes
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14. 14▶BDA 2019 Lecture 6.2 probabilistic programming and StanBayesian Data AnalysisNotes
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15. 15▶BDA 2019 Lecture 6.1 HMC, NUTS, dynamic HMC, and HMC specific convergence diagnosticsBayesian Data AnalysisNotes
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16. 16▶BDA 2019 Lecture 5.2 warm up, convergence diagnostics, R-hat, and effective sample sizeBayesian Data AnalysisNotes
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17. 17▶BDA 2019 Lecture 5.1 Markov chain Monte Carlo, Gibbs sampling, and Metropolis algorithmBayesian Data AnalysisNotes
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18. 18▶BDA 2019 Lecture 4.2 direct simulation, curse of dimensionality, rejection and importance samplingBayesian Data AnalysisNotes
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19. 19▶BDA 2019 Lecture 4.1 numerical issues, Monte Carlo, how many simulation draws are needed, ...Bayesian Data AnalysisNotes
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20. 20▶BDA 2019 Lecture 3 on multiparameter models. joint, marginal and conditional distribution, normalBayesian Data AnalysisNotes
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21. 21▶AlphaFold @ CASP13: “What just happened?”Some Thoughts on a Mysterious UniverseNotes
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