Happy to share that the second paper of my PhD is now available as preprint and open for public discussion:
https://doi.org/10.5194/egusphere-2023-222

We developed a stochastic model of regional surface heat flow and Bayesian methods for its quantification. In particular, we aim to infer the strength of a specifically shaped signal given a sample of heat flow measurements.
#geophysics #heatflow #openscience #BayesianInference

🚀 #AWS Fortuna is skyrocketing! 🚀 Just a few days, and so many GitHub stars and forks! ⭐️

Fortuna supports #ConformalPrediction, #BayesianInference and other methods for #UncertaintyQuantification in #DeepLearning.

Try it out and let us know!
https://github.com/awslabs/fortuna

In collaboration with @cedapprox, @andrewgwils and team.

#uncertainty #neuralnetworks #bayesian #conformal #calibration #jax #flax #python #opensource #library #machinelearning #ai

"Our results show that a Bayesian machine can be implemented in a system with distributed #memristors, performing computation
locally, and with min. energy movement, allowing the computation of #BayesianInference with an energy efficiency more than three orders of magnitude higher than a standard microcontroller unit. Due to its reliance on non-volatile memory, and its sole use of read ops, once [...] programmed, the system may be powered down anytime while regaining functionality instantly. "

Today, we open sourced Fortuna (https://github.com/awslabs/fortuna) a library for uncertainty quantification.
Deep neural networks are often overconfident and do not know what they don’t know. Quantifying the uncertainty in the predictions they make will help deploy deep learning more responsibly and more safely.
#responsibleAI #ConformalPrediction #BayesianInference #UncertaintyQuantification #deeplearning #opensource

Ok, I’m finally going start making a blog and writing posts about topics related to #tractability #BayesianInference #nonparametrics and #deeplearing.

🤔 Bayesian Inference (on graphical models) is NP-hard.

But even worst! every epsilon-approximation is also NP-hard.

Which means that the worst case scenario is (almost certainly) exponential.

Good news is, there are some special cases where approximation or exact inference can be performed efficiently.

📘 Check out more in "Probabilistic Graphical Models: Principles and Technique" by Daphne Koller and Nir Friedman

#Bayes #bayesianism #MachineLearning #AI #ML #BayesianInference #Inference

🚨 #inferentialstatistics 🚨

Call for proposals for the #PyMCon web series is open!

What to propose? Papers, workshops, roundtables, demos, any engaging and unique formats you can think of.

🥇 First-time speakers are encouraged!
👀 The review process will be double-blind.
📍 Submissions are due Nov. 30.

Details here: https://pymcon.com/cfp

We'd love to receive your submission. Feel free to reach out with additional questions!

#bayes #BayesianInference #inferenzstatistik #Bayesienne @pymc