#GaussianProcess

Cheng Soon Ongcheng@masto.ai
2023-09-22

We propose a new family of probability densities that have closed form normalising constants. Our densities use two layer neural networks as parameters, and strictly generalise exponential families. We show that the squared norm can be integrated in closed form, resulting in the normalizing constant. We call the densities Squared Neural Family (#SNEFY), which are closed under conditioning.

Accepted at #NeurIPS2023. #MachineLearning #Bayesian #GaussianProcess

arxiv.org/abs/2305.13552

2023-01-16

#arxivfeed :

"Neural network with optimal neuron activation functions based on additive Gaussian process regression"
arxiv.org/abs/2301.05567

#MachineLearning #DeepLearning #GaussianProcess

2023-01-06

#arxivfeed :

"Dynamic Bayesian Learning and Calibration of Spatiotemporal Mechanistic Systems"
arxiv.org/abs/2208.06528

#DynamicalSystems #ModelCalibration #Bayesian #ParameterEstimation #GaussianProcess

Cheng Soon Ongcheng@masto.ai
2022-12-19

Take the idea of random Fourier features, as applied to #GaussianProcess regression in #MachineLearning. There is a method in the probabilistic numerics textbook about Gaussian quadrature (same Gauss, different method) which gives good convergence with respect to the spectrum of a function. Show that a high quality #kernel (low rank approximation) can be computed efficiently (sublinear in the number of training points).
jmlr.org/papers/v23/21-0030.ht

Tyler James Burchtylerjburch@bayes.club
2022-11-23

Been trying out a lot of #GaussianProcess libraries in #python lately. For what my opinion is worth, I'm really enjoying using GPFlow.

It seems to have a good balance that you can customize the things you want, and not have to over-worry about the rest. Documentation includes simple examples to very advanced. Comprehensive enough for a guy like me to get a model up and running in a couple hours on real data.

Samuel Kaskisamikaski
2022-11-22

@FCAI Update on Zheyang’s status: The opponent got there on the last minute, gave an enlightening view of the position of the thesis in and es, and asked a set of broad and challenging questions. Zheyand did outstandingly well, with still some unsolved questions which he will be eager to pursue when on the job market at some point. Big congrats Zheyang Shen and many thanks opponent Chris Oates! @FCAI

Seth Axen 🪓 :julia:sethaxen@fosstodon.org
2022-11-10

Anyone know of an approach to construct a #GaussianProcess prior over strictly monotonic functions? #MachineLearning #Bayesian

2022-11-09

I have a variety of #tutorials posted on my website (peter-stewart.github.io/posts/) on a variety of topics, including a series on classic ecological #models in #Stan and #RStats, an #occupancy model which handles spatial autocorrelation using a #GaussianProcess, and a variety of useful Windows batch files for dealing with #CameraTrap images.

Here is a quick #thread 🧵 with links to the individual posts:

1/n

#BayesianStatistics #Ecology

three panel scatter plot showing observed (simulated) data vs model predictions for empty, plant-only, and plant plus disperser patches in a version of the Levins metapopulation model.
2022-11-06

@Inference Hmmm how about #gaussianprocess instead 🤔

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