Show HN: Deterministic objective Bayesian inference for spatial models [pdf] To give some context, objective Bayesian inference refers to Bayesian analysis (i.e. integrating over the parameter space) using a prior that is design to represent "minimal information" (see [1], [2], and [3] for an overview). Particularly in cases where a model's likelihood function is not strongly peaked about a point, objective Bayesian inference can give better results than methods based off of point estimates like Maximum Likelihood [4]. Reference priors provides a general approach to construct so-called noninformative priors that are suitable for Objective Bayesian analysis ([5], [6]). The approach takes a practical viewpoint of noninformative priors and looks to build priors that are both tractable and provide good performance on frequentist coverage simulations. See Section 2 for a description of how the process and frequentist simulations work and [7] for examples with some basic models (e.g. why 1/σ^2 is the noninformative prior for the variance of normally distributed data with known mean). [8] was the first to develop reference priors for Gaussian processes models, and [9] extended the work to handle Gaussian Processes with noise (or nugget effects). The project I'm working on provides software and algorithms to do deterministic inference using the prior from [9]. Typically, such inference has been done using MCMC sampling algorithms; but my belief is that deterministic algorithms can give results that are more consistent, less sensitive to parameter tweaking, and more efficient, at the expense of some engineering cost and loss of generality. For an example of how the algorithms work on a real-world data set of zinc measurements in a flood plain along the Meuse river [10], see https://ift.tt/PFwH7mU... References [1]: https://ift.tt/ytLSzwl [2]: https://ift.tt/toDP94S... [3]: https://ift.tt/5hl6piL [4]: https://ift.tt/LtUNADR... [5]: https://ift.tt/x9IUJhs... [6]: https://ift.tt/FToUNhQ [7]: https://ift.tt/VWLswPc... [8]: https://ift.tt/7SygdIt... [9]: https://ift.tt/qShuT3G... [10]: https://ift.tt/RNYvrKB... https://ift.tt/oeucsfP May 10, 2023 at 09:07PM
Show HN: Tape It, iOS recording app for musicians Hello HN, Over the last 15 months, two friends and I developed the music recording app we felt we wanted based on our own needs as musicians. It's called Tape It [1] and has just recently hit the Apple App Store [2]. We put a lot of effort into a good UX to help musicians really focus on playing their instrument instead of pretending to be a recording engineer. The app records in stereo on newer iPhones (although that's a premium feature; the free version only records in standard mono audio quality). I would be really grateful for advice from this community on how to best approach marketing. We had a great TechCrunch article covering our launch [3], and we posted it on various music websites. Turns out advertising on Google or Apple Search is a dark art, though. We have some good ideas for developing a good social media presence, but they will take time. Please hit us with feedback, opinions and advice that you think a young ind...
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