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<html>
<head>
<meta charset="utf-8">
<script src="lib/bindings/utils.js"></script>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/dist/vis-network.min.css" integrity="sha512-WgxfT5LWjfszlPHXRmBWHkV2eceiWTOBvrKCNbdgDYTHrT2AeLCGbF4sZlZw3UMN3WtL0tGUoIAKsu8mllg/XA==" crossorigin="anonymous" referrerpolicy="no-referrer" />
<script src="https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/vis-network.min.js" integrity="sha512-LnvoEWDFrqGHlHmDD2101OrLcbsfkrzoSpvtSQtxK3RMnRV0eOkhhBN2dXHKRrUU8p2DGRTk35n4O8nWSVe1mQ==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>
<center>
<h1></h1>
</center>
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<script type="text/javascript" src="../node_modules/vis/dist/vis.js"> </script>-->
<link
href="https://cdn.jsdelivr.net/npm/bootstrap@5.0.0-beta3/dist/css/bootstrap.min.css"
rel="stylesheet"
integrity="sha384-eOJMYsd53ii+scO/bJGFsiCZc+5NDVN2yr8+0RDqr0Ql0h+rP48ckxlpbzKgwra6"
crossorigin="anonymous"
/>
<script
src="https://cdn.jsdelivr.net/npm/bootstrap@5.0.0-beta3/dist/js/bootstrap.bundle.min.js"
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crossorigin="anonymous"
></script>
<center>
<h1></h1>
</center>
<style type="text/css">
#mynetwork {
width: 100%;
height: 750px;
background-color: #ffffff;
border: 1px solid lightgray;
position: relative;
float: left;
}
</style>
</head>
<body>
<div class="card" style="width: 100%">
<div id="mynetwork" class="card-body"></div>
</div>
<script type="text/javascript">
// initialize global variables.
var edges;
var nodes;
var allNodes;
var allEdges;
var nodeColors;
var originalNodes;
var network;
var container;
var options, data;
var filter = {
item : '',
property : '',
value : []
};
// This method is responsible for drawing the graph, returns the drawn network
function drawGraph() {
var container = document.getElementById('mynetwork');
// parsing and collecting nodes and edges from the python
nodes = new vis.DataSet([{"color": "#FFA500", "id": "neural networks", "label": "neural networks", "shape": "dot", "size": 40, "title": "neural networks"}, {"color": "#FFA500", "id": "computer vision", "label": "computer vision", "shape": "dot", "size": 40, "title": "computer vision"}, {"color": "#FFA500", "id": "natural language processing", "label": "natural language processing", "shape": "dot", "size": 40, "title": "natural language processing"}, {"color": "#6495ED", "id": "Geoffrey Hinton", "label": "Geoffrey Hinton", "shape": "dot", "size": 50, "title": "Geoffrey Hinton"}, {"color": "#6495ED", "id": "John J. Hopfield", "label": "John J. Hopfield", "shape": "dot", "size": 50, "title": "John J. Hopfield"}, {"color": "red", "id": "Chicago", "label": "Chicago", "shape": "dot", "size": 10, "title": "Chicago"}, {"color": "#8A2BE2", "id": "California Institute of Technology (Caltech)", "label": "California Institute of Technology (Caltech)", "shape": "dot", "size": 30, "title": "California Institute of Technology (Caltech)"}, {"color": "#8A2BE2", "id": "Princeton University", "label": "Princeton University", "shape": "dot", "size": 30, "title": "Princeton University"}, {"color": "#8A2BE2", "id": "AT\u0026T Bell Laboratories", "label": "AT\u0026T Bell Laboratories", "shape": "dot", "size": 30, "title": "AT\u0026T Bell Laboratories"}, {"color": "#FFA500", "id": "Hopfield network", "label": "Hopfield network", "shape": "dot", "size": 40, "title": "Hopfield network"}, {"color": "#F4A460", "id": "Nobel Prize in Physics", "label": "Nobel Prize in Physics", "shape": "dot", "size": 20, "title": "Nobel Prize in Physics"}, {"color": "#ADFF2F", "id": "July 15, 1933", "label": "July 15, 1933", "shape": "dot", "size": 10, "title": "July 15, 1933"}, {"color": "#FFD700", "id": "American", "label": "American", "shape": "dot", "size": 25, "title": "American"}, {"color": "#8A2BE2", "id": "Swarthmore College", "label": "Swarthmore College", "shape": "dot", "size": 30, "title": "Swarthmore College"}, {"color": "#FF6347", "id": "bachelor\u2019s degree", "label": "bachelor\u2019s degree", "shape": "dot", "size": 25, "title": "bachelor\u2019s degree"}, {"color": "#FF6347", "id": "Ph.D", "label": "Ph.D", "shape": "dot", "size": 25, "title": "Ph.D"}, {"color": "red", "id": "London", "label": "London", "shape": "dot", "size": 10, "title": "London"}, {"color": "#8A2BE2", "id": "University College London", "label": "University College London", "shape": "dot", "size": 30, "title": "University College London"}, {"color": "#8A2BE2", "id": "Carnegie Mellon University", "label": "Carnegie Mellon University", "shape": "dot", "size": 30, "title": "Carnegie Mellon University"}, {"color": "#8A2BE2", "id": "University of Toronto", "label": "University of Toronto", "shape": "dot", "size": 30, "title": "University of Toronto"}, {"color": "#8A2BE2", "id": "Vector Institute", "label": "Vector Institute", "shape": "dot", "size": 30, "title": "Vector Institute"}, {"color": "#8A2BE2", "id": "Google Brain", "label": "Google Brain", "shape": "dot", "size": 30, "title": "Google Brain"}, {"color": "#8A2BE2", "id": "University of California, San Diego", "label": "University of California, San Diego", "shape": "dot", "size": 30, "title": "University of California, San Diego"}, {"color": "#FF4500", "id": "pursuit of knowledge and innovation", "label": "pursuit of knowledge and innovation", "shape": "dot", "size": 15, "title": "pursuit of knowledge and innovation"}, {"color": "#FF4500", "id": "advisory roles", "label": "advisory roles", "shape": "dot", "size": 15, "title": "advisory roles"}, {"color": "#FF4500", "id": "research", "label": "research", "shape": "dot", "size": 15, "title": "research"}, {"color": "#FF4500", "id": "cognitive psychologist and computer scientist", "label": "cognitive psychologist and computer scientist", "shape": "dot", "size": 15, "title": "cognitive psychologist and computer scientist"}, {"color": "#FF4500", "id": "advisory role", "label": "advisory role", "shape": "dot", "size": 15, "title": "advisory role"}, {"color": "#6495ED", "id": "Ronald J. Williams", "label": "Ronald J. Williams", "shape": "dot", "size": 50, "title": "Ronald J. Williams"}, {"color": "#6495ED", "id": "David Rumelhart", "label": "David Rumelhart", "shape": "dot", "size": 50, "title": "David Rumelhart"}, {"color": "#FFA500", "id": "mixtures of experts", "label": "mixtures of experts", "shape": "dot", "size": 40, "title": "mixtures of experts"}, {"color": "#FFA500", "id": "distributed representations", "label": "distributed representations", "shape": "dot", "size": 40, "title": "distributed representations"}, {"color": "#FFA500", "id": "time delay neural networks", "label": "time delay neural networks", "shape": "dot", "size": 40, "title": "time delay neural networks"}, {"color": "#FFA500", "id": "AI applications", "label": "AI applications", "shape": "dot", "size": 40, "title": "AI applications"}, {"color": "#FFA500", "id": "the product of experts", "label": "the product of experts", "shape": "dot", "size": 40, "title": "the product of experts"}, {"color": "#FFA500", "id": "Helmholtz machines", "label": "Helmholtz machines", "shape": "dot", "size": 40, "title": "Helmholtz machines"}, {"color": "#FFA500", "id": "Boltzmann machine", "label": "Boltzmann machine", "shape": "dot", "size": 40, "title": "Boltzmann machine"}, {"color": "#6495ED", "id": "Richard Zemel", "label": "Richard Zemel", "shape": "dot", "size": 50, "title": "Richard Zemel"}, {"color": "#6495ED", "id": "Alex Krizhevsky", "label": "Alex Krizhevsky", "shape": "dot", "size": 50, "title": "Alex Krizhevsky"}, {"color": "#6495ED", "id": "Yann LeCun", "label": "Yann LeCun", "shape": "dot", "size": 50, "title": "Yann LeCun"}, {"color": "#6495ED", "id": "Brendan Frey", "label": "Brendan Frey", "shape": "dot", "size": 50, "title": "Brendan Frey"}, {"color": "#6495ED", "id": "Yoshua Bengio", "label": "Yoshua Bengio", "shape": "dot", "size": 50, "title": "Yoshua Bengio"}, {"color": "#6495ED", "id": "Ruslan Salakhutdinov", "label": "Ruslan Salakhutdinov", "shape": "dot", "size": 50, "title": "Ruslan Salakhutdinov"}, {"color": "#F4A460", "id": "Turing Award", "label": "Turing Award", "shape": "dot", "size": 20, "title": "Turing Award"}, {"color": "#F4A460", "id": "Rumelhart Prize", "label": "Rumelhart Prize", "shape": "dot", "size": 20, "title": "Rumelhart Prize"}, {"color": "#F4A460", "id": "Princess of Asturias Award", "label": "Princess of Asturias Award", "shape": "dot", "size": 20, "title": "Princess of Asturias Award"}, {"color": "#F4A460", "id": "IEEE Frank Rosenblatt Award", "label": "IEEE Frank Rosenblatt Award", "shape": "dot", "size": 20, "title": "IEEE Frank Rosenblatt Award"}, {"color": "#ADFF2F", "id": "December 6, 1947", "label": "December 6, 1947", "shape": "dot", "size": 10, "title": "December 6, 1947"}, {"color": "#FFD700", "id": "British-Canadian", "label": "British-Canadian", "shape": "dot", "size": 25, "title": "British-Canadian"}, {"color": "#6495ED", "id": "Ilya Sutskever", "label": "Ilya Sutskever", "shape": "dot", "size": 50, "title": "Ilya Sutskever"}, {"color": "#8A2BE2", "id": "University of Cambridge", "label": "University of Cambridge", "shape": "dot", "size": 30, "title": "University of Cambridge"}, {"color": "#FF6347", "id": "experimental psychology", "label": "experimental psychology", "shape": "dot", "size": 25, "title": "experimental psychology"}, {"color": "#8A2BE2", "id": "field of artificial intelligence", "label": "field of artificial intelligence", "shape": "dot", "size": 30, "title": "field of artificial intelligence"}, {"color": "#8A2BE2", "id": "Stanford University", "label": "Stanford University", "shape": "dot", "size": 30, "title": "Stanford University"}, {"color": "#6495ED", "id": "Mary Everest Boole", "label": "Mary Everest Boole", "shape": "dot", "size": 50, "title": "Mary Everest Boole"}, {"color": "#6495ED", "id": "George Boole", "label": "George Boole", "shape": "dot", "size": 50, "title": "George Boole"}, {"color": "#DC143C", "id": "responsible AI practices", "label": "responsible AI practices", "shape": "dot", "size": 20, "title": "responsible AI practices"}, {"color": "#DC143C", "id": "ethical implications of advanced technologies", "label": "ethical implications of advanced technologies", "shape": "dot", "size": 20, "title": "ethical implications of advanced technologies"}, {"color": "#FFA500", "id": "algebra of logic", "label": "algebra of logic", "shape": "dot", "size": 40, "title": "algebra of logic"}, {"color": "red", "id": "Nizhny Novgorod", "label": "Nizhny Novgorod", "shape": "dot", "size": 10, "title": "Nizhny Novgorod"}, {"color": "#8A2BE2", "id": "OpenAI", "label": "OpenAI", "shape": "dot", "size": 30, "title": "OpenAI"}, {"color": "#FF4500", "id": "Chief Scientist", "label": "Chief Scientist", "shape": "dot", "size": 15, "title": "Chief Scientist"}, {"color": "#FFA500", "id": "GPT-3", "label": "GPT-3", "shape": "dot", "size": 40, "title": "GPT-3"}, {"color": "#FFA500", "id": "GPT-4", "label": "GPT-4", "shape": "dot", "size": 40, "title": "GPT-4"}, {"color": "#ADFF2F", "id": "December 8, 1986", "label": "December 8, 1986", "shape": "dot", "size": 10, "title": "December 8, 1986"}, {"color": "#FFD700", "id": "Canadian-Israeli-Russian", "label": "Canadian-Israeli-Russian", "shape": "dot", "size": 25, "title": "Canadian-Israeli-Russian"}, {"color": "#FFA500", "id": "AlexNet", "label": "AlexNet", "shape": "dot", "size": 40, "title": "AlexNet"}, {"color": "#6495ED", "id": "Howard Everest Hinton", "label": "Howard Everest Hinton", "shape": "dot", "size": 50, "title": "Howard Everest Hinton"}, {"color": "#00BFFF", "id": "father", "label": "father", "shape": "dot", "size": 15, "title": "father"}, {"color": "#FF4500", "id": "entomologist", "label": "entomologist", "shape": "dot", "size": 15, "title": "entomologist"}, {"color": "#FFA500", "id": "backpropagation algorithm", "label": "backpropagation algorithm", "shape": "dot", "size": 40, "title": "backpropagation algorithm"}, {"color": "#DC143C", "id": "large language models like ChatGPT", "label": "large language models like ChatGPT", "shape": "dot", "size": 20, "title": "large language models like ChatGPT"}, {"color": "#DC143C", "id": "self-driving cars", "label": "self-driving cars", "shape": "dot", "size": 20, "title": "self-driving cars"}, {"color": "red", "id": "Soisy-sous-Montmorency", "label": "Soisy-sous-Montmorency", "shape": "dot", "size": 10, "title": "Soisy-sous-Montmorency"}, {"color": "#8A2BE2", "id": "Courant Institute of Mathematical Sciences at New York University", "label": "Courant Institute of Mathematical Sciences at New York University", "shape": "dot", "size": 30, "title": "Courant Institute of Mathematical Sciences at New York University"}, {"color": "#8A2BE2", "id": "Meta (formerly Facebook)", "label": "Meta (formerly Facebook)", "shape": "dot", "size": 30, "title": "Meta (formerly Facebook)"}, {"color": "#FF4500", "id": "key figure in deep learning", "label": "key figure in deep learning", "shape": "dot", "size": 15, "title": "key figure in deep learning"}, {"color": "#FF4500", "id": "computer scientist", "label": "computer scientist", "shape": "dot", "size": 15, "title": "computer scientist"}, {"color": "#FFA500", "id": "DjVu image compression technology", "label": "DjVu image compression technology", "shape": "dot", "size": 40, "title": "DjVu image compression technology"}, {"color": "#ADFF2F", "id": "July 8, 1960", "label": "July 8, 1960", "shape": "dot", "size": 10, "title": "July 8, 1960"}, {"color": "#FFD700", "id": "French-American", "label": "French-American", "shape": "dot", "size": 25, "title": "French-American"}, {"color": "#FFA500", "id": "convolutional neural networks (CNNs)", "label": "convolutional neural networks (CNNs)", "shape": "dot", "size": 40, "title": "convolutional neural networks (CNNs)"}, {"color": "#8A2BE2", "id": "University of Edinburgh", "label": "University of Edinburgh", "shape": "dot", "size": 30, "title": "University of Edinburgh"}, {"color": "#FF6347", "id": "AI", "label": "AI", "shape": "dot", "size": 25, "title": "AI"}]);
edges = new vis.DataSet([{"from": "neural networks", "title": "developed", "to": "computer vision", "width": 4}, {"from": "neural networks", "title": "developed", "to": "natural language processing", "width": 4}, {"from": "neural networks", "title": "developed", "to": "Geoffrey Hinton", "width": 4}, {"from": "John J. Hopfield", "title": "bornIn", "to": "Chicago", "width": 4}, {"from": "John J. Hopfield", "title": "worksAt", "to": "California Institute of Technology (Caltech)", "width": 4}, {"from": "John J. Hopfield", "title": "worksAt", "to": "Princeton University", "width": 4}, {"from": "John J. Hopfield", "title": "worksAt", "to": "AT\u0026T Bell Laboratories", "width": 4}, {"from": "John J. Hopfield", "title": "developed", "to": "Hopfield network", "width": 4}, {"from": "John J. Hopfield", "title": "collaboratedWith", "to": "Geoffrey Hinton", "width": 4}, {"from": "John J. Hopfield", "title": "hasAward", "to": "Nobel Prize in Physics", "width": 4}, {"from": "John J. 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Hopfield", "title": "earnedDegree", "to": "Ph.D", "width": 4}, {"from": "Geoffrey Hinton", "title": "bornIn", "to": "London", "width": 4}, {"from": "Geoffrey Hinton", "title": "worksAt", "to": "University College London", "width": 4}, {"from": "Geoffrey Hinton", "title": "worksAt", "to": "Carnegie Mellon University", "width": 4}, {"from": "Geoffrey Hinton", "title": "worksAt", "to": "University of Toronto", "width": 4}, {"from": "Geoffrey Hinton", "title": "coFounded", "to": "Vector Institute", "width": 4}, {"from": "Geoffrey Hinton", "title": "workedWith", "to": "Google Brain", "width": 4}, {"from": "Geoffrey Hinton", "title": "worksAt", "to": "University of California, San Diego", "width": 4}, {"from": "Geoffrey Hinton", "title": "hasRole", "to": "pursuit of knowledge and innovation", "width": 4}, {"from": "Geoffrey Hinton", "title": "hasRole", "to": "advisory roles", "width": 4}, {"from": "Geoffrey Hinton", "title": "hasRole", "to": "research", "width": 4}, {"from": "Geoffrey Hinton", "title": "hasRole", "to": "cognitive psychologist and computer scientist", "width": 4}, {"from": "Geoffrey Hinton", "title": "hasRole", "to": "advisory role", "width": 4}, {"from": "Geoffrey Hinton", "title": "coAuthored", "to": "Ronald J. 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Williams", "title": "invented", "to": "backpropagation algorithm", "width": 4}, {"from": "AI applications", "title": "characteristics", "to": "large language models like ChatGPT", "width": 4}, {"from": "AI applications", "title": "characteristics", "to": "self-driving cars", "width": 4}, {"from": "Yann LeCun", "title": "bornIn", "to": "Soisy-sous-Montmorency", "width": 4}, {"from": "Yann LeCun", "title": "worksAt", "to": "Courant Institute of Mathematical Sciences at New York University", "width": 4}, {"from": "Yann LeCun", "title": "worksAt", "to": "Meta (formerly Facebook)", "width": 4}, {"from": "Yann LeCun", "title": "hasRole", "to": "key figure in deep learning", "width": 4}, {"from": "Yann LeCun", "title": "hasRole", "to": "computer scientist", "width": 4}, {"from": "Yann LeCun", "title": "coAuthored", "to": "Yoshua Bengio", "width": 4}, {"from": "Yann LeCun", "title": "developed", "to": "DjVu image compression technology", "width": 4}, {"from": "Yann LeCun", "title": "hasAward", "to": "Turing Award", "width": 4}, {"from": "Yann LeCun", "title": "bornAt", "to": "July 8, 1960", "width": 4}, {"from": "Yann LeCun", "title": "hasNationality", "to": "French-American", "width": 4}, {"from": "Yann LeCun", "title": "workedWith", "to": "convolutional neural networks (CNNs)", "width": 4}, {"from": "University of Edinburgh", "title": "earnedDegreeFrom", "to": "AI", "width": 4}]);
nodeColors = {};
allNodes = nodes.get({ returnType: "Object" });
for (nodeId in allNodes) {
nodeColors[nodeId] = allNodes[nodeId].color;
}
allEdges = edges.get({ returnType: "Object" });
// adding nodes and edges to the graph
data = {nodes: nodes, edges: edges};
var options = {
"configure": {
"enabled": false
},
"edges": {
"color": {
"inherit": true
},
"smooth": {
"enabled": true,
"type": "dynamic"
}
},
"interaction": {
"dragNodes": true,
"hideEdgesOnDrag": false,
"hideNodesOnDrag": false
},
"physics": {
"enabled": true,
"forceAtlas2Based": {
"avoidOverlap": 0,
"centralGravity": 0.015,
"damping": 0.4,
"gravitationalConstant": -31,
"springConstant": 0.08,
"springLength": 100
},
"solver": "forceAtlas2Based",
"stabilization": {
"enabled": true,
"fit": true,
"iterations": 1000,
"onlyDynamicEdges": false,
"updateInterval": 50
}
}
};
network = new vis.Network(container, data, options);
return network;
}
drawGraph();
</script>
</body>
</html>