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the weights in the output layer through a sequence of functional evaluations over the weights from previous layers. During training, the machine learning algorithm uses optimization to minimize a loss function, where the loss function depends on the difference between the weights in the output layer and the expected values. Node graphs are used to visualize, configure and debug these neural network layers.
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399:. Another survey focuses on peoples beliefs on the cognitive effects of visual programming, in which they found that professional programmers are the most skeptical of visual programming. Other studies have shown in psychological experiments that visual programming can have significant positive effects on performance in cognitive tasks.
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applications. The diagram above shows a simple neural network composed of 3 layers. The 3 layers are the input layer, the hidden layer, and the output layer. The elements in each layer are weights and are connected to weights in other layers. During inference, the machine learning algorithm evaluates
330:
In the paper
Hierarchical Small Worlds in Software Architecture author Sergi Valverde argues that most large software systems are built in a modular and hierarchical fashion, and that node graphs can be used to analyze large software systems. Many other software analysis papers often use node graphs
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in the same as other nodes. This node simply groups a subset of connected nodes together and manages the inputs and outputs into or out of the group. This hides complexity inside of the group nodes and limits their coupling with other nodes outside the group. This leads to a hierarchy where smaller
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Research studies tend to shed more details on these discussions and highlight more of the advantages and disadvantages of node graphs. They indicate that node graphs and visual programming are easy to understand for new users, but as the users move to more complex tasks they often need to resort to
154:
as to the benefits of visual programming and node graph architecture. Advocates highlight how the abstraction that node graphs provide makes the tool easier to use. Critics highlight how visual programming is too restrictive and how they must resort to modifying source code or scripts to accomplish
1637:). In this software's operational model, a video sequence is being passed through the lines onto the next node, and each node performs some additional modifications to the video sequence. In this example one video is translated in 2D, another is pixelated, and finally, both streams are merged.
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With the increasing usage of node graphs, there is currently increased attention on creating user-friendly interfaces. Often these new interfaces are being designed by user interface specialists and graphical designers. The following are some user interfaces designed by artists and designers.
210:
A program's execution need not be controlled by the usual explicit sequential flow conventions. The movement of data through a program may determine its operation. A data controlled convention corresponds closely to our intuitive ideas of how a graphical program should operate and also allows
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Some of the more recent uses of node graph architectures started around 2005. Node graphs in this time frame start to develop paradigms to deal with complexity in the node graph. The complexity arose as the number of nodes and links in the graph increased. One of the main ideas dealing with
362:
Advocates of visual programming generally emphasize how it simplifies programming because it abstracts away many details and only exposes controls that are necessary for their domain. These controls are the parameters on the nodes which control their behavior and the links between
423:
refers to an organization of software functionality into atomic units known as nodes, and where nodes can be connected to each other via links. The manipulation of nodes and links in the node graph can be often be accomplished through a programmable
779:
Mathematically they can be thought of as additional input values to the node's compute function. The only difference is that these values are controlled directly by the user instead of being output by another node as a by-product of its
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The ease of debugging programs, particularly parallel ones, will be enhanced by a pictorial language form. Being able to attach data probes and to see a program run gives one a grasp of detail that is hard to obtain in any other
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Important organizational concepts in the GRAIL system are the sequential flow of control, the hierarchy of subroutines, and the language (flow diagrams) for pictorially relating the organization within the concepts of the first
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Visually the node's parameters are often exposed after the user clicks on the node. This helps to reduce visually cluttering the node graph. In the diagram above we see a parameter window opening up beside the "Add Star" node.
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Visually nodes are often represented by rectangles. However, this is not a convention that is followed by all applications. In the diagram above there are three nodes labeled "Video", "Add Star" and "Add Circle".
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industries. The diagram above shows a simplified user interface for an artistic tool for editing and creating videos. The nodes are represented as rectangles and are connected to each other through curved lines
100:
its operation on these inputs to produce its own outputs. The ability to link nodes together in this way allows complex tasks or problems to be broken down into atomic nodal units that are easier to understand.
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The sequential nature of control allows the man to envision isolated processes that are adapted to specific functions--which, in turn, allow the organizer to think of the total program in terms of manageable
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workflows or programs. Since then his thesis has been used as "prior art" in order to quash lawsuits about dataflow ideas today. His work is often thought to have led the way to what is known as
784:. For example, in the simple example above regarding a node that adds two numbers, we can introduce a bias parameter on the node so that the node can add an extra fixed number onto the sum.
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between different nodes. They are analogous to mathematical composition. For example, if node A is feeding its outputs to node B, this can be represented mathematically as follows.
358:
industries node graphs are synonymous with visual programming. There is currently some debate on the power, abstraction, and need of node graphs and visual programming languages.
175:. The effort attempts to document the evolution and explosion of node graph user interfaces starting from their initial roots. This visual history is hosted on a blog page called
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using node graph architecture will typically expose the node graph visually or graphically to the user, allowing the user to make changes to the node graph. Using the
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A pictorial program is a natural way of expressing parallel processes. The two-dimensional nature of the language helps in visualizing many things happening at once.
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graphs are embedded in group nodes. The following are examples of group nodes which are used to group a subset of connected nodes and to help simplify the graph.
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In modern-day usage, the term "node graph" is an open compound word. However, in older software it was referred to as a "nodegraph", a closed compound word.
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This remains an active area of debate with new discussions occurring in open forums to this day. The following are a few of the largest discussions to date.
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Flow diagrams help the man to picture his control options and the relationship between processes by expressing these interrelationships in two dimensions.
179:. Work leading to node graph architectures and visual programming seems to have started in the 1960s, in the area known as "man-machine communications".
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Katana, a popular look and lighting software, includes hundreds of nodes. each performing specific tasks related to lighting computer graphics scenes.
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Critics of visual programming generally emphasize how it does not offer enough control, and how for more complex tasks it becomes necessary to author
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463:. A simple example is a node that adds two numbers together. The inputs are the two numbers to add and the output is the sum of the two numbers.
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complexity was the concept of a group or package node which hid nodes inside of itself, only exposing the inputs and outputs of the group.
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to analyze large software systems suggesting that node graphs are good models of the internal structure and operation of the software.
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232:. The GRAIL system used a flowchart-based graphical programming language and could recognize handwritten letters and gestures.
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by following links. To avoid these problems many node graphs architectures restrict themselves to a subset of graphs known as
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Mari, a popular 3D painting software, includes hundreds of nodes. each performing specific tasks related to 3D painting.
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are designed around the editing and composition (or linking) of atomic functional units. Node graphs are a type of
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1475:. There are often many different node types participating in the node graph. The following are some examples:
346:. Node graphs allow you to design programs in a visual and structured way instead of through the authoring of
186:, he describes and analyses topics around a 2D pictorial language. This is one of the first investigations in
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Palsingh, Rishi; Vandana, Vandana (2014). "Application of Graph Theory in
Computer Science and Engineering".
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The most important node type for managing complexity is the group node. This node type does not execute
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are the main adopters of this software design with the majority of tools using node graph architecture.
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Valverde, Sergi; Sole, Ricard V. (11 July 2003). "Hierarchical Small Worlds in
Software Architecture".
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370:. However, these more complex tasks often fall outside the intended usage or domain of the node graph.
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132:. Nodes are often drawn as rectangles, and connections between nodes are drawn with lines or splines.
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Mathematically the node's inputs and outputs are analogous to input and output values of functions.
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for all inputs and all outputs. Outputs and inputs can refer to each other, typically by holding
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for all nodes. Each node can have inputs and outputs, which are typically also implemented using
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1592:. When cycles are present in the node graph, the evaluation never ends as nodes are continually
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will often visually display the node graph to the user. This is often accomplished by using the
2276:"Implementing a Reverse Dictionary, based on word definitions, using a Node-Graph Architecture"
1956:"Strengths and weaknesses of a visual programming language in a learning context with children"
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Many theoretical results from graph theory apply to node graphs, especially with regards to
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William Robert
Sutherland's MIT thesis (1966) "Online Graphical Specification of Procedures"
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to perform the rendering which is subsequently displayed on the desktop to the user. Common
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program, includes hundreds of nodes. each performing specific tasks related to compositing.
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Nodes often have inputs and outputs, as discussed above. Inputs and outputs are backed by
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The subroutine hierarchy emphasizes the notion of isolated processes even more strongly.
228:, a system where users could write computer commands directly on a tablet, conducted by
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2199:"Graph Grammars and Constraint Solving for Software Architecture Styles". 1998: 69–72.
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In 1969, T. O. Ellis, J. F. Heafner, and W. L. Sibley published a paper concerning a
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is organized into atomic functional units called nodes. This is typically done using
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functionality and will often take inputs and produce outputs as a by-product of
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804:. Inputs and outputs are crucial to storing values before and after the node's
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started in the 1960s. Today the use of node graphs has exploded. The fields of
2022:"Metacognitive theories of visual programming: what do we think we are doing?"
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Visually the inputs and outputs of nodes are often represented with circles.
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stored in its inputs to retrieve data output by other nodes. The node then
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The type of a node indicates which compute operation it will perform when
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1264:{\displaystyle {outputs}_{nodeB}=f_{nodeB}(f_{nodeA}({inputs}_{nodeA}))}
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432:. In the diagram above, the node graph appears on the right-hand side.
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129:
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Metrics of
Software Architecture Changes Based on Structural Distance
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Nodes are analogous to mathematical functions of the following form.
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1972:"Visual programming: the outlook from academia and industry". 1997.
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240:, however, he was not involved with the creation of the system.
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One particular area of concern during node graph evaluation is
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to collect snapshots of all node graph user interfaces in most
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Nodes perform some type of computation. They encapsulate this
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117:
935:{\displaystyle {outputs}_{nodeA}=f_{nodeA}({inputs}_{nodeA})}
590:{\displaystyle {outputs}_{nodeA}=f_{nodeA}({inputs}_{nodeA})}
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its functionality, it retrieves its inputs by following the
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The on-line graphical specification of computer procedures
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Nodes often have additional parameters, that define their
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parallel programming without explicit flow designations.
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Proceedings 1996 IEEE Symposium on Visual
Languages
1724:without a graphical interface for the node graphs.
1352:are the operations performed by node B and node A,
1640:The following are some examples of software using
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1819:(Thesis). Massachusetts Institute of Technology.
1612:An example of a node graph based user interface
2237:International Journal of Computer Applications
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16:Software design structured around a node graph
1406:is a vector of the node A's input values and
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8:
144:
2317:"Representation and Analysis of Software".
1885:"Representation and Analysis of Software".
1463:is a vector of the node B's output values.
1038:is a vector of the node's input values and
693:is a vector of the node's input values and
428:or through a visual interface by using the
2274:Thorat, Sushrut; Choudhari, Varad (2016).
2138:"Nuke: Grouping Nodes with the Group Node"
1942:"Visual Programming - Why it's a Bad Idea"
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306:Blender (software) § Geometry Nodes
177:Visual Programming Languages - Snapshots
88:of other outputs or inputs. When a node
2194:Representation and Analysis of Software
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1540:view the current output values on nodes
1537:evaluate the graph up to a certain node
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342:are a subset of the broader class of
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1708:has recently become very popular in
1524:, users will typically be able to:
1108:Links transfer the values stored in
315:Grasshopper, McNeel & Associates
1813:Sutherland, William Robert (1966).
1739:The following are some examples of
1762:Deep Cognition, Deep Congition Inc
37:structured around the notion of a
14:
1928:"Visual Programming Doesn't Suck"
1090:{\displaystyle {outputs}_{nodeA}}
768:. These parameters are backed by
745:{\displaystyle {outputs}_{nodeA}}
1848:"GRAIL Graphical Input Language"
220:. Their work was related to the
218:Graphical Input Language (GRAIL)
1456:{\displaystyle outputs_{nodeB}}
384:Discussion on Hacker News, 2019
379:Discussion on Hacker News, 2014
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38:
1716:The following are examples of
1569:Example directed acyclic graph
1399:{\displaystyle inputs_{nodeA}}
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1031:{\displaystyle inputs_{nodeA}}
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686:{\displaystyle inputs_{nodeA}}
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163:There is an ongoing effort by
1:
1624:is especially popular in the
224:which began with research on
1772:Neural Network Console, Sony
1696:Simple neural network layers
1581:are linked together to form
344:visual programming languages
1767:Neural Network Modeler, IBM
984:is the node's computation,
639:is the node's computation,
192:computer-aided design (CAD)
150:To this day, there is some
51:visual programming language
2399:
2368:What is visual programming
1825:1721.1/13474?show=full
1734:TensorFlow, GitHub, Google
1577:. This subject area where
1484:visual effects compositing
326:Abstraction and Complexity
1729:PyTorch, GitHub, Facebook
1345:{\displaystyle f_{nodeA}}
1306:{\displaystyle f_{nodeB}}
977:{\displaystyle f_{nodeA}}
632:{\displaystyle f_{nodeA}}
440:Nodegraph, Valve Software
335:Visual Programming Debate
238:demos of the GRAIL system
2162:"Katana: Grouping Nodes"
2090:"Katana Reference Guide"
2020:Blackwell, A.F. (1996).
1789:Adobe Substance Designer
1604:Use in Computer Graphics
1531:edit parameters on nodes
271:Blender node graph, 2006
1757:PerceptiLabs, KDnuggets
1745:node graph architecture
1722:node graph architecture
1702:node graph architecture
1688:Use in Machine Learning
1642:node graph architecture
1618:node graph architecture
1598:directed acyclic graphs
1561:Directed Acyclic Graphs
1550:Node graphs on Dribbble
792:Node Inputs and Outputs
389:Reddit discussion, 2019
137:node graph architecture
31:Node graph architecture
2340:Cite journal requires
2304:Cite journal requires
2222:Cite journal requires
2114:"Mari Reference Guide"
2066:"Nuke Reference Guide"
2034:10.1109/VL.1996.545293
2001:Cite journal requires
1908:Cite journal requires
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1613:
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1534:connect nodes together
1508:Group nodes in Katana.
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1978:10.1145/266399.266415
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411:An example node graph
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2028:. pp. 240–246.
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2142:learn.foundry.com
2118:learn.foundry.com
2094:learn.foundry.com
2070:learn.foundry.com
1585:is well studied.
1555:Nodes on Dribbble
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1657:Katana, Foundry
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286:Houdini, SideFX
281:Katana, Foundry
230:Ivan Sutherland
161:
141:graphics, games
68:derived from a
35:software design
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2183:References
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2147:2020-12-21
2123:2020-12-21
2099:2020-12-21
2075:2020-12-21
1650:video game
1630:video game
1467:Node Types
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356:video game
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