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Questions tagged [topology]

Use for questions involving topology in any form in relation to Artificial Intelligence.

2
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1answer
32 views

Is a calculus or ML approach to varying learning rate as a function of loss and epoch been investigated?

Many have examined the idea of modifying learning rate at discrete times during the training of an artificial network using conventional back propagation. The goals of such work have been a balance ...
1
vote
1answer
50 views

How can AI be used to more reliably analyze and plan around the tie between climate and emissions?

Note to the Duplicate Police This question is not a duplicate of the Q&A thread referenced in the close request. The only text even remotely related in that other thread is the brief mention of ...
4
votes
0answers
37 views

Deep Networks and generalisation of Hopfield Networks

Hopfield Nets are able to store a vector and retrieve it starting from a noisy version of it. They do so setting weights in order to minimise the energy function when all neurons are set equal the ...
6
votes
1answer
84 views

Is topological sophistication necessary to the furtherance of AI?

The current machine learning trend is interpreted by some who are new in the disciplines of AI as meaning that orthogonal structures like ANNs, CNNs, and RNNs can exhibit human intelligence. It is ...
5
votes
2answers
85 views

In what ways is the term “topology” applied to Artificial Intelligence?

I have a only a general understanding of General Topology, and want to understand the scope of the term "topology" in relation to the field of Artificial Intelligence. In what ways are topological ...
3
votes
1answer
34 views

Will attention based networks prevail over RNN and LSTM?

There is no point in picking one of the growing number of articles that come up in a web search for, "Deep learning attention networks," however the bold claims in Attention Is All You Need, Ashish ...
4
votes
1answer
75 views

What topologies support recognition of action sequences?

The ability to recognize an object with particular identifying features from single or multiple camera shoots with the temporal dimension digitized as frames has been shown. The proof is that the ...
1
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0answers
25 views

Is anyone working on officiated team intelligence or anything like it?

The artificial intelligence topology that does not appear in the machine learning literature to my knowledge is that of officiated teams or round robins of them. The paradigm is a proven one in the ...
1
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0answers
61 views

Steps recognition

What AI concepts, topologies1, algorithms, or SaaS can be used to recognize a person eating a chocolate. For this question, image recognition draws from a real time feed, validating each of these ...
5
votes
1answer
149 views

What topologies are largely unexplored in machine learning?

Geometry and AI Matrices, cubes, layers, stacks, and hierarchies are what we could accurately call topologies. Consider topology in this context the higher level geometrical design of a learning ...
3
votes
1answer
97 views

Finding goals in Hierarchical Reinforcement Learning

In a recent paper Data-Efficient Hierarchical Reinforcement Learning, O Nachum, S Gu, H Lee, S Levine, 2018, a promising agent controlling technique called Hierarchical Reinforcement Learning was ...
6
votes
3answers
301 views

How are Artificial Neural Networks and the Biological Neural Networks similar and different?

I've heard multiple times that "Neural Networks are the best approximation we have to model the human brain", and I think it is commonly known that Neural Networks are modelled after our brain. I ...
0
votes
1answer
68 views

How to evaluate output of unlayered NN?

I used to work with 'traditional' layered neural network and I evaluated the output given certain inputs by processing layer-by-layer. With NEAT, a neural network may assume any topology and they are ...
0
votes
0answers
91 views

Number of hidden layers/neurons for Connect4 Neural Networks

I have developed a neural network program to evolve neural nets to play connect 4. I have 42 input nodes, each one corresponding to a disc on the board which can either be occupied by red (-1), empty ...
5
votes
1answer
59 views

Framework for Joining Multiple Modular Artificial Neural Networks

I'm looking for an industry standard framework for joining multiple neural networks in a modular way. Assume we have two or more neural networks trained to perform certain tasks. By feeding the ...
1
vote
1answer
219 views

Neuro-evolution: Is it not Supervised Learning?

If I compare back-propagation to feed-forward neuro-modulation, the latter is unsupervised in that it requires no labeled data set. Applying to it a genetic algorithm to refine topology and weights, ...
6
votes
4answers
174 views

What are some alternative information processing system beside neural network

By "neural network", I mean the typical, multilayered neural network with inputs, weights, hidden nodes and outputs, as shown in the image below: Such neural networks, in the context of evolving ...
10
votes
2answers
334 views

How can I plan the topology of a neural network for a given “random” problem?

Assume that I want to solve an issue with neural network that either I can't fit to already existing topologies (perceptron, Konohen, etc) or I'm simply not aware of the existence of those or I'm ...
2
votes
2answers
49 views

Is there a way to define the boundaries of the optimal size of a training set?

At a related question in Computer Science SE, a user told: Neural networks typically require a large training set. Is there a way to define the boundaries of the "optimal" size of a training set ...
1
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0answers
95 views

Number of input variables for a cellular automaton (was: Squares or hexagonal?)

A cellular automaton is a state machine which is controlled by external input. The input is given by geometrical space around a cell. In a square matrix, each automaton gets input from 4 surrounding ...