Top new questions this week:
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I intend to implement CNN like progressively expanded neural network in Keras. The basic idea is the first input node can be decomposed into multiple nodes with different orders and coefficient, then ...
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I am trying to understand the formulation of the maximum entropy Inverse RL method by Brian Ziebart. Particularly, I am stuck on how to understand the computation of state - visitation frequencies.
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From what I've figured
(a) converting mathematical theorems and proofs from English to formal logic is a straightforward job for mathematicians with sufficient background, except that it takes time.
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I know that this has been asked a hundred times before, however, I was not able to find a question (and an answer) which actually answered what I wanted to know, respectively, which explained it in a ...
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As per a post, image-to-image translation is a type of CV problem.
I guess I understand the concept of image-to-image translation.
I am aware that GANs(generative adversarial networks) are good ...
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After spending some time reading about POMDP, I'm still having a hard time understanding how grid-based solutions work.
I understand the finite horizon brute-force solution, where you have your ...
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From my understanding, maximum likelihood estimation chooses the set of parameters for the estimator that maximizes likelihood with the ground truth distribution.
I always interpreted it as the ...
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Greatest hits from previous weeks:
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In the context of evolutionary computation, in particular genetic algorithms, there are two stochastic operations "mutation" and "crossover". What are the differences between them?
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I'm struggling to understand the GAN loss function as provided in Understanding Generative Adversarial Networks (a blog post written by Daniel Seita).
In the standard cross-entropy loss, we have an ...
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Is it possible to feed a neural network the output from a random number generator and expect it learn the hashing (or generator) function, so that it can predict what will be the next generated ...
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What are the differences between the A* algorithm and the greedy best-first search algorithm? Which one should I use? Which algorithm is the better one, and why?
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I am training LSTM Nets with Keras on a small mobile GPU. The speed on GPU is slower then on CPU. I found some articles that say that it is hard to train LSTMs (RNNs) on GPUs because the training ...
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Imagine you show a neural network a picture of a lion 100 times and label with "dangerous", so it learns that lions are dangerous.
Now imagine that previously you have shown it millions of images of ...
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Why is search important in AI? What kinds of search algorithms are used in AI? How do they improve the result of an AI?
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Can you answer these questions?
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Soon I will be working on biomedical image segmentation (microscopy images). There will be a small amount of data (a few dozens at best). My question is really straightforward: is there a neural ...
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I am wondering how can I find the appropriate reward value for each specific problem. I know this is a highly empirical process, but I am sure that the value is not set totally at random. I want to ...
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I want to integrate my environment into the OpenAI's gym and then use the stable baselines library for training it.
The learning method in the stable baseline is with one-line learning and you don't ...
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