Before I head off on a trip to various parts of not-Barcelona, I thought I’d share a somewhat provocative paper by David Hogg and Soledad Villar. In my capacity as journal editor over the past few years I’ve noticed that there has been a phenomenal increase in astrophysics papers discussing applications of various forms of Machine Leaning (ML). This paper looks into issues around the use of ML not just in astrophysics but elsewhere in the natural sciences.
The abstract reads:
Machine learning (ML) methods are having a huge impact across all of the sciences. However, ML has a strong ontology – in which only the data exist – and a strong epistemology – in which a model is considered good if it performs well on held-out training data. These philosophies are in strong conflict with both standard practices and key philosophies in the natural sciences. Here, we identify some locations for ML in the natural sciences at which the ontology and epistemology are valuable. For example, when an expressive machine learning model is used in a causal inference to represent the effects of confounders, such as foregrounds, backgrounds, or instrument calibration parameters, the model capacity and loose philosophy of ML can make the results more trustworthy. We also show that there are contexts in which the introduction of ML introduces strong, unwanted statistical biases. For one, when ML models are used to emulate physical (or first-principles) simulations, they introduce strong confirmation biases. For another, when expressive regressions are used to label datasets, those labels cannot be used in downstream joint or ensemble analyses without taking on uncontrolled biases. The question in the title is being asked of all of the natural sciences; that is, we are calling on the scientific communities to take a step back and consider the role and value of ML in their fields; the (partial) answers we give here come from the particular perspective of physics
arXiv:2405.18095
P.S. The answer to the question posed in the title is probably “yes”.
My Harvard Horizons video is now on YouTube! I worked hard on this with some talented animators, really excited to share it with ya'll :)
This is a short, public talk of my research: exploring connections between galaxies and cosmology with @desisurvey. https://www.youtube.com/watch?v=BIB0F_oNxdM
Finally, after months of work, the #ESAEuclid Early Release Observation images, data, first science results, and #Euclid mission reference papers have been released. You can read more in our blog post, which has links to the papers, the press releases, and everything else:
#Cosmology folk: the universe as-is exists because the very early stages had density variations, stuff clumped. That's fairly obvious, the odds of the universe being perfectly evenly distributed are basically impossible, only one way to do it (and, quantum, not even allowed?)
So what's the thinking on how unlikely our "unclumpiness" is? Compared to...I don't know, perfect homogeneity versus weirdly clumpy?
Could recent information about dark energy fundamentally alter our understanding of the universe? It's possible. Here's a deep dive into what dark energy is and how new results on the expansion history of the universe may change everything we thought we knew.
1112 authors for a space mission 🛰️ reference paper seems ... adequate 🤷🏽😯😁
We, the @ec_euclid will publish five main reference papers aimed at the astronomy community about the #ESAEuclid mission, the #Euclid instruments, both cosmology and other astronomy science possibilities, as well as the cosmological simulations used to test all procedures.
Available coming Tuesday, 23 May, 12:00 CEST (and on arXiv a few hours later). Stay tuned!
Copies of Worlds of IF Science Fiction Magazine #177, the relaunch issue, spotted in Paris. Front cover art by Bob Eggleton, back cover art by Andrew Stewart. Check out that table of contents.
Feels so good to read it in prints!
"Nasa has released footage simulating what it's like being sucked into a black hole, a region of space with such strong gravity not even light can escape." #Astronomy#Cosmology#BlackHoles#NASA