Page **1** of **2**

### Machine Learning and the physical sciences

Posted: **May 20th, 2019, 12:07 pm**

by **ISayMoo**

https://arxiv.org/abs/1903.10563
A review. Tishby is a known ML researcher, I don't know the rest of the crew.

### Re: Machine Learning and the physical sciences

Posted: **May 20th, 2019, 1:43 pm**

by **Cuchulainn**

A lot of text, pictures and references. Who is the target reader group?

Not much maths to chew on.. They use the well-known equation (!).Interesting that they mention Langevin dynamics but they don't delve into it. It would be nice to show how the two are related with the exception of a 3-line summary.

I like this style applied to a simple problem with a beginning, middle and end.

https://www.researchgate.net/publicatio ... l_equation
(Something completely different! Looking at the equations and the style of the lemmas, I just realise

*now* that I proposed the problems and lemmas way back in 1976..Blast from the past. Documented in my C++ 2004 book pages 132-138.Based on this simple ODE allowed to discover exponential fitting for PDEs and Black Scholes.)

### Re: Machine Learning and the physical sciences

Posted: **May 21st, 2019, 6:44 pm**

by **Cuchulainn**

Here's a question.: what's the major difference between a Bayesian Netwiork and a Neural Network?

### Re: Machine Learning and the physical sciences

Posted: **May 21st, 2019, 7:46 pm**

by **katastrofa**

Bayesian networks represent causal reasoning (see Pearl's DAGs), hence a much more complex problem than what's done with NNs. And no, they weren't developed by the ML community (the methods and dedicated libraries are much older - Metropolis–Hastings algorithm was what year?).

### Re: Machine Learning and the physical sciences

Posted: **May 21st, 2019, 8:30 pm**

by **mtsm**

Looks like a very biased review by a bunch of people who assimilate the physical sciences as being condensed matter physics... Pretty much. There is a large number of fields forming part of physical sciences where I can see this sh!t being useful, too.

Did you mean a Bayesian network or a Bayesian neural network? They are not the same.

### Re: Machine Learning and the physical sciences

Posted: **May 21st, 2019, 9:01 pm**

by **katastrofa**

Can you see "neural" between "Bayesian" and "network" in his question?

### Re: Machine Learning and the physical sciences

Posted: **May 21st, 2019, 9:18 pm**

by **Cuchulainn**

Did you mean a Bayesian network or a Bayesian neural network? They are not the same.

No, And if they were the same one would be redundant.

I am a mathematician and I try to avoid redundant words. I'm sure someone has tried to glue NNs with a posterior but my hunch is that it is a nasty fix and has no theoretical foundations.

It's similar to called an initial value problem for an ODE a Cauchy problem (only for ODEs). ODEs always have initial or boundary conditions.I call it "title inflation"

*A Cauchy problem in mathematics asks for the solution of a partial differential equation that satisfies certain conditions that are given on a hypersurface in the domain.*
The big difference IMO is BNs use DAGs while NNs are flat as pancake. They can't hold paths. You can't fit much structure into GD. See Cauchy's original article.

https://www.math.uni-bielefeld.de/docum ... claude.pdf

### Re: Machine Learning and the physical sciences

Posted: **May 21st, 2019, 9:36 pm**

by **Cuchulainn**

I would say that "Bayesian neural network" was coined by some anonymous blogger. People googled and started using the term? Then it starts to lead a life of its own.

### Re: Machine Learning and the physical sciences

Posted: **May 22nd, 2019, 12:50 am**

by **bearish**

Bayesian networks represent causal reasoning (see Pearl's DAGs), hence a much more complex problem than what's done with NNs. And no, they weren't developed by the ML community (the methods and dedicated libraries are much older - Metropolis–Hastings algorithm was what year?).

Metropolis 1953, Hastings 1970.

### Re: Machine Learning and the physical sciences

Posted: **May 22nd, 2019, 7:17 am**

by **ISayMoo**

### Re: Machine Learning and the physical sciences

Posted: **May 22nd, 2019, 3:14 pm**

by **katastrofa**

Bayesian networks represent causal reasoning (see Pearl's DAGs), hence a much more complex problem than what's done with NNs. And no, they weren't developed by the ML community (the methods and dedicated libraries are much older - Metropolis–Hastings algorithm was what year?).

Metropolis 1953, Hastings 1970.

Thank you, Professar Bearish! I was being rhetorically lazy

### Re: Machine Learning and the physical sciences

Posted: **May 22nd, 2019, 4:34 pm**

by **Cuchulainn**

Is MH a special case of MCMC? "Constructors" for BNs?

### Re: Machine Learning and the physical sciences

Posted: **May 22nd, 2019, 11:46 pm**

by **katastrofa**

It's a type of an MCMC method / an implementation of an MCMC algorithm(?). Those methods are simple and straightforward.

### Re: Machine Learning and the physical sciences

Posted: **May 23rd, 2019, 1:42 pm**

by **mtsm**

You're not a mathematician cuch, you're some kind of engineer. You're the guy with the wrench and the duct tape...

You need to do some googling about Bayesian neural nets also...

### Re: Machine Learning and the physical sciences

Posted: **May 23rd, 2019, 3:19 pm**

by **Cuchulainn**

Small dogs bark the loudest. No wonder everyone ignores you. Why don't you say something righteous and hopeful for a change?