Attribute Promote

Attribute Promote geometry node Promotes or demotes attributes from one geometry level to another. On this page Parameters Examples This provides a straightforward way to convert an attribute from one class to another. For example, a point attribute can be converted to a primitive attribute, using any one of a number of different merge methods. … Read more Attribute Promote


 
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VOP nodes

VOP nodes VOP node VOP nodes let you define a program (such as a shader) by connecting nodes together. Houdini then compiles the node network into executable VEX code. Source: VOP nodes


 
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Attribute VOP – Visual Programming

Attribute VOP geometry node Runs a VOP network to modify geometry attributes. Double-click this node to build a VOP network inside. (Alternatively, you can specify a SHOP node containing the VOP network, or specify a .vfl file containing the CVEX program.) Note The VOP network runs in the CVEX context, not the SOP context. This … Read more Attribute VOP – Visual Programming


 
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MAI*MA Using Monte Carlo Method

The first thoughts and attempts I made to practice [the Monte Carlo Method] were suggested by a question which occurred to me in 1946 as I was convalescing from an illness and playing solitaires. The question was what are the chances that a Canfield solitaire laid out with 52 cards will come out successfully? After spending a lot of time trying to estimate them by pure combinatorial calculations, I wondered whether a more practical method than “abstract thinking” might not be to lay it out say one hundred times and simply observe and count the number of successful plays. This was already possible to envisage with the beginning of the new era of fast computers, and I immediately thought of problems of neutron diffusion and other questions of mathematical physics, and more generally how to change processes described by certain differential equations into an equivalent form interpretable as a succession of random operations. Later [in 1946], I described the idea to John von Neumann, and we began to plan actual calculations.[14]

https://en.wikipedia.org/wiki/Monte_Carlo_method?wprov=sfti1

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The Brains Behind AI: Yoshua Bengio

The Brains Behind AI: Yoshua Bengio Could AI solve the mystery of human and animal intelligence? Canada CIFAR AI Chair Yoshua Bengio is pioneering research in deep learning and is one of the brains behind artificial neural networks, an approach that teaches computers to mimic human intelligence. Yoshua is co-director and fellow of CIFAR’s Learning … Read more The Brains Behind AI: Yoshua Bengio


 
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The Brains Behind AI: Hugo Larochelle

The Brains Behind AI: Hugo Larochelle Machines learn best when they have lots of data, but large datasets are not always easy to come by. Canada CIFAR AI Chair Hugo Larochelle is advancing research in few shot learning, a technique commonly employed in computer vision. Hugo is looking at ways to make systems faster and … Read more The Brains Behind AI: Hugo Larochelle


 
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The Brains Behind AI: Hugo Larochelle

The Brains Behind AI: Hugo Larochelle Machines learn best when they have lots of data, but large datasets are not always easy to come by. Canada CIFAR AI Chair Hugo Larochelle is advancing research in few shot learning, a technique commonly employed in computer vision. Hugo is looking at ways to make systems faster and … Read more The Brains Behind AI: Hugo Larochelle


 
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Maîtrise en informatique – Université de Montréal

Les études au niveau de la maîtrise visent une spécialisation dans un domaine de l’informatique au moyen de cours avancés. Elles ont pour but d’initier l’étudiant à la recherche par l’exploration d’un sujet limité et la rédaction d’un mémoire. Il est également possible dans l’option Générale modalité Stage d’effectuer un stage en entreprise de deux … Read more Maîtrise en informatique – Université de Montréal


 
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The Brains Behind AI: Hugo Larochelle

The Brains Behind AI: Hugo Larochelle Machines learn best when they have lots of data, but large datasets are not always easy to come by. Canada CIFAR AI Chair Hugo Larochelle is advancing research in few shot learning, a technique commonly employed in computer vision. Hugo is looking at ways to make systems faster and … Read more The Brains Behind AI: Hugo Larochelle


 
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This thing is -270°C and is EVERYWHERE on YouTube

This thing is -270°C and is EVERYWHERE Physics Girl The universe is microwaving itself. A mystery signal discovered in the 1960s led to a Nobel prize. Download the PBS Video App: https://ift.tt/2zU8oJZ In this video, Dianna explores one of the most mysterious discoveries in physics – a constant microwave signal that seemed to be coming … Read more This thing is -270°C and is EVERYWHERE on YouTube


 
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