Questions tagged [deep-neural-networks]

For questions related to deep neural networks, which are artificial neural networks with "many" layers, where "many" can vary depending on the context.

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24 views

The MLP output of a neural network can be written as $\|x\|\|w_l\|\cos(\theta_l)$: why is the norm easier to maximize?

The MLP output of a neural network is a dot product between the weights and the input and therefore can be written as $\|x\|\|w_l\|\cos(\theta_l)$ (see this for more details), where $x$ is the input, $...
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34 views

SAGAN - is there a mistake in the original paper?

in the original paper the following scheme of the self-attention appears: https://arxiv.org/pdf/1805.08318.pdf In a later overview: https://arxiv.org/pdf/1906.01529.pdf this scheme appears: ...
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15 views

How to have a DNN output a classification for each user at once?

I have a Reinforcement Learning environment with an agent that allocates power values to different users. To do so, I have thought of implementing a deep neural network like the one shown in the ...
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31 views

Can Deep Q-Learning be used to follow a predetermined path in a continuous environment?

I'm coding an agent (a serpent-like, maybe earthworm-like thing) that learns how to move around. In 1 dimension, this seems easy enough, it just has to flail around forwards. In 2D, though, there's no ...
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32 views

How to implement neural network using FPGA? [closed]

I want to design neural networks using FPGAs and make neuromorphic chip. Is there a tutorial or course to learn how to do that and to implement neural network using FPGA especially for evaluating the ...
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26 views

What's up with Neural Stochastic Differential Equations from a practical standpoint?

I've spent a few days reading some of the new papers about Neural SDEs. For example, here is one from Tzen and Raginsky and here is one that came out simultaneously by Peluchetti and Favaro. There are ...
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2answers
70 views

How do we know that the neurons of an artificial neural network start by learning small features?

I'd like to ask you how do we know that neural networks start by learning small, basic features or "parts" of the data and then use them to build up more complex features as we go through ...
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16 views

How to augment 2.5D keypoints?

I am currently working on 3D hand pose estimation. The idea is to first detect the 2.5D pose representation and then obtain 3D pose with the help of camera parameters. For some reason, I was trying to ...
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25 views

Are all activation functions in a layer same? [duplicate]

I understand that for you can have multiple activation functions in different layers. CNN's usually have Relu followed by softmax for the classification. But what stops us in having multiple ...
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45 views

Estimating dimensions to reduce input image size to in CNNs

Considering input images to a CNN that have a large dimension (e.g. 256X256), what are some possible methods to estimate the exact dimensions (e.g. 16X16 or 32X32) to which it can be condensed in the ...
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17 views

How to deal with dynamically changing input tensor in neural networks without padding?

I have a dataset about the monitored health/growth of a community of people. The dataset has tensor shaped (batch_size, features, person, window), where: person==...
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42 views

Are there any new weight initialization techniques for DNN published after 2015?

Considering weights initialization in my personal projects, I always used some standard techniques such as: Glorot (also known as Xavier) initialization (2010). Mertens initialization (2010). He ...
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1answer
70 views

Regression For Elliptical Curve Public Key Generation Possible?

As part of a learning more about deep learning, I have been experimenting with writing ResNets with Dense layers to do different types of regression. I was interested in trying a harder problem and ...
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22 views

How should I use deep learning to find the rotation of an object from its 2D image?

I have 6600 images and I am supposed to know the rotation of the object in each image. So, given an image, I want to regress to a single value. My attempt: I use Resnet-18 to extract a feature vector ...
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33 views

CNN for a DQN agent with a 2D matrix state and action as a 2D matrix

I have a custom environment, where the state is a 2D matrix of 11 rows (equals to number of users to satisfy) and 3 columns. Each column can take the value of either 0 or 1, and in each row, there can ...
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1answer
99 views

How to build a DQN agent with state and action being arrays?

I have a Reinforcement-Learning environment where the state is an array of 0s and 1s with length equals to the number of users the agent must satisfy (11 users). The agent must choose one of 12 ...
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49 views

DQN Agent with a 2D matrix as input in Keras

I have a Reinforcement Learning environment where the state is a 2D matrix with 0s and 1s (only one column with the value of 1 in each row). Example: ...
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1answer
41 views

What are the conceptual differences between regularisation and optimisation in deep neural nets?

I'm trying to wrap my mind around the concepts of regularisation and optimisation in neural nets, especially around their differences. In my current understanding, regularisation is intended to tackle ...
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1answer
140 views

In GradCAM, why is activation strength considered an indicator of relevant regions?

In the GradCAM paper section 3 they implicitly propose that two things are needed to understand which areas of an input image contribute most to the output class (in a multi-label classification ...
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64 views

Am I using transfer learning when I use SSD ResNet 50 model architecture?

Using Label-img, I have successfully labeled my images (dimensions 1100 x 1100 pixels), and am currently training the SSD ResNet50 model (from the TensorFlow 2 Detection Model Zoo). I downloaded the ...
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1answer
59 views

DQN layers when state space and action space are multi dimensional

I have built my own RL environment, where a state is composed of two elements: the agent's position and a matrix of 0s and 1s (1 if a user has requested a service from the agent, 0 otherwise); an ...
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1answer
33 views

How is the performance of a model affected by adding a ReLU to fully connected layers?

How significant is adding a ReLU to fully connected (FC) layers? Is it necessary, or how is the performance of a model affected by adding ReLU to FC layers?
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9 views

Is there a framework or method that would help visualise inner workings of a feedforward neural network?

I wonder if there is some framework or method to help visualising inner workings of a feedforward deep neural network? What I mean by this is something similar to what is being done with CNNs where we ...
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36 views

How to use Deep Q-Network with two-dimensional input? Hands-on Machine Learning 2

I'm studying with the book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow, and I'm trying to implement the Deep Q-Network example that can be found on Github but that the input ...
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1answer
31 views

Are there deep neural networks that have inputs connected with deeper hidden layers?

Are there any architectures of deep neural networks that connect input neurons not only with first hidden layer but also with deeper ones (red lines on the picture)? If so could you give some names ...
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1answer
62 views

Has “deep vs. wide” been resolved?

All else being equal, including total neuron count, I give the following definitions: wide is a parallel ensemble, where good chunks of the neurons have the same inputs because the inputs are shared ...
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36 views

Deep Continuous Clustering algorithm - just one output cluster

I use the DCC algorithm to cluster some data. The whole algorithm is available here, but shortly it is: construct mkNN graph of the data points (the connected components of it are the clusters). ...
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1answer
102 views

What exactly is an interpretable machine learning model?

From this page in Interpretable-ml book and this article on Analytics Vidhya, it means to know what has happened inside an ML model to arrive at the result/prediction/conclusion. In linear regression, ...
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1answer
46 views

What are the rules behind vector product in gradient?

Let's suppose we have calculated the gradient and it came out to be $f(WX)(1-f(W X))X$, where $f()$ is the sigmoid function, $W$ of order $2\times2$ is the weight matrix, and $X$ is an input vector of ...
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1answer
75 views

What are the mathematical prerequisites needed to understand research papers on neural networks? [closed]

I know we have developed some mathematical tools to understand deep neural networks, gradient descent for optimization, and basic calculus. Recently, I encountered arxiv paper that describes higher ...
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1answer
51 views

Why does using a higher representation space lead to performance increase on the training data but not on the test data?

I read the following from a book: You can intuitively understand the dimensionality of your representation space as “how much freedom you’re allowing the model to have when learning internal ...
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30 views

How to understand this NN architecture?

I was reading a paper Multi-Agent Reinforcement Learning for Adaptive User Association in Dynamic mmWave Networks and I was stuck understanding the deep neural network architecture that was used. The ...
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1answer
50 views

What type of model should I fit to increase accuracy?

Currently, I'm working on 6-axis IMU(Inertial Measurment Unit) dataset. This dataset contain 6 axis IMU data of 7 different drivers. The Imu sensor attached on vehicle. The drivers drives same path. ...
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1answer
26 views

How is weighted average computed in Deep Q networks

I was going through the Sutton book and they said the update formula for Q learning comes from the weighted average of the returns I.e New estimate= old estimate +alpha*[returns- old estimate] So by ...
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15 views

How can I decrease the time to compute the mask in the Mask-RCNN for human body detection?

I am using Mask-RCNN to detect human bodies in photos, to get a rough approximation of the ratio of their heights to the length of their chests. I want to decrease the time for making the mask of the ...
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11 views

Generative Adversarial Network with two images in input

I am doing an internship project regarding deep learning, and it is a totally new topic for me as I have never studied machine learning in the bachelor's degree courses. I have to implement a GAN that ...
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2answers
180 views

My Deep Q-Learning Network does not learn for OpenAI gym's cartpole problem

I am implementing OpenAI gym's cartpole problem using Deep Q-Learning (DQN). I followed tutorials (video and otherwise) and learned all about it. I implemented a code for myself and I thought it ...
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1answer
148 views

What is the state-of-the-art algorithm for neural style transfer?

I've read the paper A Neural Algorithm of Artistic Style by Gatys et. al. and I find the application of neural style transfer very fun. I also read that Exploring the structure of a real-time, ...
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36 views

Why do we use the Target Network for action evaluation in Double deep Q networks

Is there any specific reason as to why The target Network is used for evaluation and The online network Is used for selection, what would be the difference if both roles were switched, our online ...
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1answer
124 views

Why does not the deepAR model of Amazon require the time series being stationary, as opposed to ARMA model?

As what the title said. Does not deepAR require the time series being stationary?
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45 views

Possible reasons that validation recall is fluctuating across different epochs but the precision is stable?

I'm training a deep learning model. After each epoch I measure the performance of the model on validation set. Here is how the performance looks like while training: It's a binary classification task ...
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41 views

How can one be sure that a particular neural network architecture would work?

Traditionally, when working with tabular data, one can be sure(or at least know) that a model works because the included features could explain a target variable, say "Price of a ticket" ...
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46 views

Advantages of training Neural Networks based on analytic success criteria

What is the reason to train a Neural Network to estimate a task's success (i.e. robotic grasp planning) using a simulator that is based on analytic grasp quality metrics? Isn't a perfectly trained NN ...
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1answer
353 views

Why do we need target network in deep Q learning? [duplicate]

I already know deep RL, but to learn it deeply I want to know why do we need 2 networks in deep RL. What does the target network do? I now there is huge mathematics into this, but I want to know deep ...
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39 views

DQN Tic-Tac-Toe does not quite become optimal

I am trying to implement a DQN agent for playing standard 3x3 Tic-Tac-Toe (it is a double DQN with experience replay, and using a target network). I got the hyperparameters to the point where the ...
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22 views

Computational difference between ANN and Pattern Matching

Conceptually, if you had an internal 3d model of all objects in CV you could do a scan matching algorithm. This algorithm would be ridiculously computationally intensive, but it would have a high ...
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53 views

Why are YOLO Darknet weights so heavy?

I have been trying to understand how YOLO Darknet works, and for the most part reading the documentation and checking the code helps me understand. But when it comes to the weight file, I can't find ...
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17 views

Separated LSTMs or a global one for cluster of related features

I have an $n$-dimensional time-series to apply LSTM to, $n$ is the number of features for each time point. These features can be clustered according to their concept, for example $n_1, ..., n_4$ are ...
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1answer
159 views

Can we use a pre trained Encoder (BERT, XLM ) with a Decoder (GPT, Transformer-XL) to build a Chatbot instead of Language Translation?

I was wondering if the BART or T5 models can do the task of generating sentences in English. Most of the models I have mentioned ...
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1answer
70 views

What's the right way of building a deep Q-network?

I'm new to RL and to deep q-learning and I have a simple question about the architecture of the neural network to use in an environment with a continous state space a discrete action space. I tought ...