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Enforcing stability constraints in set

Generative adversarial networks GANs are initially proposed to generate images by learning from a large number of samples. Recently, GANs have been used to emulate complex physical systems such as turbulent flows. However, a critical question must be answered before GANs can be considered trusted emulators for physical systems: do GANs-generated samples conform to the various physical constraints?

These include both deterministic constraints e. The latter has been studied in a companion paper Wu et al. Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical systems. In the present work, we enforce deterministic yet approximate constraints on GANs by incorporating them into the loss function of the generator.

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We evaluate the performance of physics-constrained GANs on two representative tasks with geometrical constraints generating points on circles and differential constraints generating divergence-free flow velocity fieldsrespectively. In both cases, the constrained GANs produced samples that precisely conform to the underlying constraints, even though the constraints are only enforced approximately.

More importantly, the imposed constraints significantly accelerate the convergence and improve the robustness in the training. These improvements are noteworthy, as the convergence and robustness are two well-known obstacles in the training of GANs. Zeng Yang. Jin-Long Wu. Heng Xiao. Simulating complex physical systems often involves solving partial diffe The problem of finding distributions of input parameters for determinist We assume that we are given a time series of data from a dynamical syste Generative adversarial networks, which can generate metasurfaces based o Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.

Machine learning and particularly deep learning has achieved significant success in a wide range of commercial domain applications such as image recognition, audio recognition, and natural language processing. For example, machine learning methods such as random forests and neural networks have been used to provide closure models for turbulent flows. The scientific applications reviewed above mostly involve supervised learningwhich consists of three steps:.

Recently, a dramatically different type of machine learning models referred to as generative models have found wide-spread applications in commercial and scientific domains. Generative models such as GANs construct mappings from a generic e. This is in stark contrast to supervised learning, which constructs functional mappings from input features to outputs based on labeled data.

enforcing stability constraints in set

Once trained, such models can generate new samples that are not in the training database but conform to the data distribution. As the training only uses unlabeled data, generative models belong to unsupervised learning. In the past few years, GANs have achieved major successes in commercial domain applications such as computer graphics. It also quickly found applications in scientific domains.

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The successful applications to physics prompt a critical question on the capability of GANs: do they generate samples that conform to the underlying physical constraints? These constraints are implicitly embedded in the training data to certain accuracy, because the data are obtained either by solving the equations that describe these constraints or by directly observing the physical system that obey such constraints. However, the constraints are not explicitly encoded in the GANs. In the above-mentioned applications, the generated output are physical fields that often reside in high-dimensional spaces.

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This is in contrast to supervised learning, where the output are multi-class labels or low-dimensional scalar and vectors e. Consequently, numerous efforts have been made to improve the stability and robustness in training GANs, leading to a number of GANs variants.

In contrast, the present work investigates the feasibility of using physical constraints to improve the training of GANs used to emulate physical systems.

It is expected that our work will complement existing works in regularizing the training of physics-emulating GANs. The current work advocates using physical constraints to improve the robustness of training GANs.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information.

I have two Django models, each with a foreign key to the other one. Deleting instances of a model returns an error because of the foreign key constraint:. As it might resulted in data inconsistency. For example, it will be very helpful when you are uploading large amount of data using a mysqldump output. I normally only disable foreign key constraints when I want to truncate a table, and since I keep coming back to this answer this is for future me:.

That will accomplish a similar thing and you wouldn't have to turn key checking on and off. Like so:. A very simple solution with phpMyAdmin :. I was still having a com. If the key field is nullable, then you can also set the value to null before attempting to delete it:. In phpMyAdmin you can select multiple rows and can then click the delete action.

You'll enter a screen which lists the delete queries. It looks like this:. Please uncheck the "Enable foreign key checks" checkbox, and click on Yes to execute them. It's not a good idea to set a foreign key constraint to 0, because if you do, your database would not ensure it is not violating referential integrity. This could lead to inaccurate, misleading, or incomplete data. You make a foreign key for a reason: because all the values in the child column shall be the same as a value in the parent column.

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Since every student must have a user id, it would make sense to make the student id from the student accounts table a foreign key that references the primary key user id in the user ids table. If there are no foreign key checks, a student could end up having a student id and no user id, which means a student can get an account without being a user, which is wrong. It's best to figure out what is causing the error.In the meantime, start building your store with a free 14-day trial of Shopify.

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enforcing stability constraints in set

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enforcing stability constraints in set

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enforcing stability constraints in set

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Contact us Previews All previews Tip game Compare odds News Preview Bonus.Google can probably compute and identify that one a lot faster than you can its so obvious. A useful links page out to unrelated sites on a low-quality domain is just spam to Google and more often or not the pages your links are on will just be ignored by Google, so there is no point getting a link from these pages.

Linking is the foundation of the web. Without links, there would be no web as we know it, no Google even, so never be scared of linking to useful sites or pages. In fact, Google WANTS or, at least, EXPECTS you to do this and will thank you for it at some level. Do you really want that. Of course, you should ALWAYS be LOOKING for high-quality links, whether you link back to those sites or not. One-way links are better for ranking in search engines as they indicate editorially approved links from other sites to yours.

I am working with a client at the moment in a global market that makes something amazing a lot of blue chip companies pay a lot of money for. The aim is to get the BRAND websites to VOTE for our site FIRST, so OUR search engine rankings improve, because Google now TRUSTS our site because of these new quality links on sites it already trusts.

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I think all Brand managers would like another good-news-page in the SERPs, so creating a case study for their brand, on your website, is probably better than a link on a links page Google will probably eventually ignore.

If a very trusted site links to my site and gave me a ranking boost, am I expected to believe that linking back to them will remove my ranking boost. Linking back to a site that links to you is a very common thing on the web.

Consider the small site that links to its industry body, and a year down the line the small site is a big player, with links from the industry body. Is that link useless. I would think Google is a lot smarter than that, at some level. I think Google would, at all times, take into account the trust and authority of the sites in question, and whether or not it has any reason not to trust the sites.

I never link to a site JUST BECAUSE THEY LINK TO ME, because the chances are, they are linking to ANY site out there regardless or not if it is a bad neighbourhood.

Google reserves the right to penalise you badly if you link to one of these, or are linked from one of them. Of course, you could robots. Back To Table Of ContentsThe best piece of advice I can give you is to FOCUS ON BUILDING A LINKABLE ASSET and VARY your linking strategy while ensuring to avoid low-quality links.

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Anchor Text Anchor text is simply the text in the link. I would encourage it, rather than overtly advertise it. Remember, too, that what Google can easily identify in your link profile, it can penalise, filter or demote your for. Contextual Link within text, surrounded by text Google can easily spot a long list of links (like navigation arrays, etc. Ideally, the surrounding text would also be relevant to my page.

The thinking is, trusted sites rank well in Google, because they are, well, trusted. If you can manage to get a link from a trusted site in your niche, this could be worth its weight in Gold. How do you tell if a website (or page within a website) is trusted.




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