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1500 questions
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Which neural networks can be used only for storing and retrieving information?
Is there a neural network(NN) system or architecture which can be used for only storing and retrieving information. For example; to store whole Avatar movie in HD format inside a neural network and retrieve(without loss) it from the neural network…
Eka
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Is there any programming language designed by deep learning?
I know that AI can be used to design printed circuit boards (PCBs), so it can be used to solve complex tasks.
Is there any programming language designed by deep learning (or any other AI technique)?
sailfish009
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What is a good way to create an artificial self-recognition?
Self-Recognition seems to be an item that designers are trying to integrate into artificial intelligence. Is there a generally recognized method of doing this in a machine, and how would one test the capacity - as in a Turing-Test?
D. Wade
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Emulating human brain - with analogous NN chips
Considering the answers of this question, emulating a human brain with the current computing capacity is currently impossible, but we aren't very far from it.
Note, 1 or 2 decades ago, similar calculations had similar results.
The clock frequency of…
peterh
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How should I deal with variable-length inputs for neural networks?
I am a very beginner in the field of AI. I am basically a Pharma Professional without much coding experience. I use GUI-based tools for the neural network.
I am trying to develop an ANN that receives as input a protein sequence and produces as…
Swayamprakash Patel
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Can neurons in MLP and filters in CNN be compared?
I know they are not the same in working, but an input layer sends the input to $n$ neurons with a set of weights, based on these weights and the activation layer, it produces an output that can be fed to the next layer.
Aren't the filters the same,…
Tibo Geysen
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1 answer
What are pros and cons of Bi-LSTM as compared to LSTM?
What are the pros and cons of LSTM vs Bi-LSTM in language modelling? What was the need to introduce Bi-LSTM?
DRV
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6
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1 answer
If vanishing gradients are NOT the problem that ResNets solve, then what is the explanation behind ResNet success?
I often see blog posts or questions on here starting with the premise that ResNets solve the vanishing gradient problem.
The original 2015 paper contains the following passage in section 4.1:
We argue that this optimization difficulty is unlikely…
Alexander Soare
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How to correctly implement self-play with DQN?
I have an environment where an agent faces an equal opponent, and while I've achieved OK performance implementing DQN and treating the opponent as a part of the environment, I think performance would improve if the agent trains against itself…
Pell000
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How can the policy iteration algorithm be model-free if it uses the transition probabilities?
I'm actually trying to understand the policy iteration in the context of RL. I read an article presenting it and, at some point, a pseudo-code of the algorithm is given :
What I can't understand is this line :
From what I understand, policy…
Samuel Beaussant
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How to define an action space when an agent can take multiple sub-actions in a step?
I'm attempting to design an action space in OpenAI's gym and hitting the following roadblock. I've looked at this post which is closely related but subtly different.
The environment I'm writing needs to allow an agent to make between $1$ and $n$…
Seyed Moein Ayyoubzadeh
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How exactly does self-play work, and how does it relate to MCTS?
I am working towards using RL to create an AI for a two-player, hidden-information, a turn-based board game. I have just finished David Silver's RL course and Denny Britz's coding exercises, and so am relatively familiar with MC control, SARSA,…
Alienator
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2 answers
What are the state-of-the-art meta-reinforcement learning methods?
This question can seem a little bit too broad, but I am wondering what are the current state-of-the-art works on meta reinforcement learning. Can you provide me with the current state-of-the-art in this field?
Sara El
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Why is the evidence equal to the KL divergence plus the loss?
Why is the equation $$\log p_{\theta}(x^1,...,x^N)=D_{KL}(q_{\theta}(z|x^i)||p_{\phi}(z|x^i))+\mathbb{L}(\phi,\theta;x^i)$$ true, where $x^i$ are data points and $z$ are latent variables?
I was reading the original variation autoencoder paper and I…
user8714896
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2 answers
In deep learning, is it possible to use discontinuous activation functions?
In deep learning, is it possible to use discontinuous activation functions (e.g. one with jump discontinuity)?
(My guess: for example, ReLU is non-differentiable at a single point, but it still has a well-defined derivative. If an activation…
Gyeonghoon Ko
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