Questions tagged [topology]

For questions involving topology in any form in relation to Artificial Intelligence.

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Is it possible to know the family of functions a neural network approximates?

Is it possible somehow to find which family of functions a particular network approximates? For example, I have some directed graph and I use its vertices as artificial neurons (as simple McCulloch &...
Just do it's user avatar
1 vote
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Comparing Auto-regressive Encoder-Decoders and Topological Neural Networks

I am interested in what insights can be gained about the mathematical class of auto-regressive encoder-decoders (LLMs), by comparing them to topological neural networks. Specifically, I am looking for ...
Julius Hamilton's user avatar
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Nearest neighbour search in high dimension retrieves certain points too often

We represent some catalogue items (documents, music tracks, videos, whatever) as vectors embedded in R^d and use them to retrieve nearest neighbours to users query. The typical scenario is that users ...
Peter Franek's user avatar
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Behaviour of PPO/similar Algos under action penalties

I am currently experimenting with PPO in different environments. I am interested in learning policies that fulfill a certain goal while keeping a specific value low. Here's an example: Using PPO on a ...
Lukas Schroth's user avatar
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How do I use the N correctly in NEATs speciation delta function?

When implementing NEAT I'm having some issues with the speciation distance/delta function, specifically the term N (number of genes in biggest genome). Won't term $N$ in $δ=c1*E/N+c2*D/N+c3*W$ just ...
egil87's user avatar
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Is it possible to find a good neural network structure without training it? [duplicate]

Neural networks consist of so many parameters. Researchers could create as many possible neural networks as they wish. So I want to ask a general question. Could we devise an evolutionary algorithm ...
bitWise's user avatar
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Are there any animation tools available to visualise and simulate deep neural networks? [closed]

Deep learning researchers have to work with a lot of models. The models may include different types of Layers: They include convolutional neural network layers, recurrent neural network layers, batch ...
hanugm's user avatar
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Is there any application of topology to deep learning?

Is there any application of topology (as in math discipline) to deep learning? If so, what are some examples?
SpiderRico's user avatar
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19 votes
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Are Modular Neural Networks more effective than large, monolithic networks at any tasks?

Modular/Multiple Neural networks (MNNs) revolve around training smaller, independent networks that can feed into each other or another higher network. In principle, the hierarchical organization ...
Harsh Sikka's user avatar
2 votes
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zonal or template ocr invoices reading

I'd like to explore the possibilities of applying artificial intelligence to ocr reading. Basic ocr invoices processing let me convert 30% of them only. The main purpose is defining invoices areas by ...
Gab's user avatar
  • 21
2 votes
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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 ...
Douglas Daseeco's user avatar
4 votes
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Neural networks of arbitrary/general topology?

Usually neural networks consist from layers, but is there research effort that tries to investigate more general topologies for connections among neurals, e.g. arbitrary directed acyclic graphs (DAGs)....
TomR's user avatar
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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 ...
Douglas Daseeco's user avatar
11 votes
1 answer

Can layers of deep neural networks be seen as Hopfield networks?

Hopfield networks are able to store a vector and retrieve it starting from a noisy version of it. They do so setting weights in order to minimize the energy function when all neurons are set equal to ...
Mario Alemi's user avatar
8 votes
2 answers

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

I have 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 ...
DukeZhou's user avatar
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4 votes
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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 ...
Douglas Daseeco's user avatar
1 vote
1 answer

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

A cellular automaton is a state machine that 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 ...
kenorb's user avatar
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