Category Archives: computation

Series, symmetrized Normalized Compressed Divergences and their logit transforms

(Major update on 11th January 2019. Minor update on 16th January 2019.) On comparing things The idea of a calculating a distance between series for various purposes has received scholarly attention for quite some time. The most common application is … Continue reading

Posted in Akaike Information Criterion, bridge to somewhere, computation, content-free inference, data science, descriptive statistics, divergence measures, engineering, George Sughihara, information theoretic statistics, likelihood-free, machine learning, mathematics, model comparison, model-free forecasting, multivariate statistics, non-mechanistic modeling, non-parametric statistics, numerical algorithms, statistics, theoretical physics, thermodynamics, time series | 4 Comments

These are ethical “AI Principles” from Google, but they might as well be `technological principles’

This is entirely adapted from this link, courtesy of Google and Alphabet. Objectives Be socially beneficial. Avoid creating or reinforcing unfair bias. Be built and tested for safety. Be accountable to people. Incorporate privacy design principles. Uphold high standards of … Continue reading

Posted in American Statistical Association, artificial intelligence, basic research, Bayesian, Boston Ethical Society, complex systems, computation, corporate citizenship, corporate responsibility, deep recurrent neural networks, emergent organization, ethical ideals, ethics, extended producer responsibility, friends and colleagues, Google, Google Pixel 2, humanism, investments, machine learning, mathematics, moral leadership, natural philosophy, politics, risk, science, secularism, technology, The Demon Haunted World, the right to know, Unitarian Universalism, UU, UU Humanists | Leave a comment

Papers of the day

From the Machine Learning and Computational Modeling Lab, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran: A. Ahmadian, K. Fouladi, B. N. Araabi, “Writer identification using a probabilistic model of handwritten digits and Approximate Bayesian Computation,” International … Continue reading

Posted in American Association for the Advancement of Science, American Statistical Association, approximate Bayesian computation, Bayesian, civilization, computation, denial, education, engineering, evidence, free flow of labor, physics, science, science education, statistics | Leave a comment

“Full-depth Ocean Heat Content” reblog

This is a re-blog of an excellent post at And Then There’s Physics, titled Full-depth OHC or, expanded, “full-depth ocean heat content”. Since my holiday is now over, I thought I might briefly comment on a recent paper by Cheng … Continue reading

Posted in Anthropocene, climate, climate change, climate data, climate disruption, climate models, computation, differential equations, ensembles, environment, fluid dynamics, forecasting, geophysics, global warming, greenhouse gases, Hyper Anthropocene, Lorenz, Mathematics and Climate Research Network, model comparison, NOAA, oceanography, physics, science, statistics, theoretical physics, thermodynamics, time series | Leave a comment

HadCRUT4 and GISTEMP series filtered and estimated with simple RTS model

Happy Vernal Equinox! This post has been updated today with some of the equations which correspond to the models. An assessment of whether or not there was a meaningful slowdown or “hiatus” in global warming, was recently discussed by Tamino … Continue reading

Posted in AMETSOC, anemic data, Bayesian, boosting, bridge to somewhere, cat1, changepoint detection, climate, climate change, climate data, climate disruption, climate models, complex systems, computation, data science, dynamical systems, geophysics, George Sughihara, global warming, hiatus, information theoretic statistics, machine learning, maths, meteorology, MIchael Mann, multivariate statistics, physics, prediction, Principles of Planetary Climate, rationality, reasonableness, regime shifts, sea level rise, time series | 5 Comments

high dimension Metropolis-Hastings algorithms

If attempting to simulate from a multivariate standard normal distribution in a large dimension, when starting from the mode of the target, i.e., its mean γ, leaving the mode γis extremely unlikely, given the huge drop between the value of the density at the mode γ and at likely realisations Continue reading

Posted in Bayes, Bayesian, Bayesian inversion, boosting, chance, Christian Robert, computation, ensembles, Gibbs Sampling, James Spall, Jerome Friedman, Markov Chain Monte Carlo, mathematics, maths, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical software, numerics, optimization, reasonableness, Robert Schapire, SPSA, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, Yoav Freund | Leave a comment

El Nino In A Can – Dan’s Wild Wild Science Journal – AGU Blogosphere

Click the image above to see a video from the GFDL CM2.6 climate model. This is NOT this year’s El Nino. When you start a climate model in which the ocean and the land and atmosphere can inte… Source: El … Continue reading

Posted in AMETSOC, astrophysics, climate, climate change, climate models, computation, Dan Satterfield, differential equations, diffusion, diffusion processes, dynamical systems, ENSO, environment, forecasting, geophysics, global warming, Hyper Anthropocene, Kerry Emanuel, mathematics, maths, mesh models, meteorology, model comparison, NASA, NCAR, NOAA, numerical analysis, oceanography, physics, Principles of Planetary Climate, rationality, Ray Pierrehumbert, reasonableness, science, Spaceship Earth, stochastics, supercomputers, the right to know, thermodynamics, time series | Leave a comment

“1D Wave with Delta Potential and Triangle Initial Position” (Jeff Galkowski, Stanford)

The latest calculations from Jeff Galkowski, of Stanford.

Posted in computation, engineering, Jeff Galkowski, mathematics, maths, McGill University, numerical analysis, numerical software, physics, proud dad, quantum, scattering, science, Stanford University, the right to know, University of California Berkeley, University of Rochester, wave equations, waves | Leave a comment

The CWSLab workflow tool: an experiment in community code development

Originally posted on Dr Climate:
Give anyone working in the climate sciences half a chance and they’ll chew your ear off about CMIP5. It’s the largest climate modelling project ever conducted and formed the basis for much of the IPCC…

Posted in climate, climate education, climate models, computation, differential equations, dynamical systems, environment, forecasting, geophysics, global warming, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, NCAR, oceanography, open source scientific software, physics, Principles of Planetary Climate, Python 3, rationality, reasonableness, science, science education, state-space models, statistics, time series, transparency | Leave a comment