Questions tagged [tensorflow]

A Python library for deep learning developed by Google. Use this tag for any on-topic question that (a) involves tensorflow either as a critical part of the question or expected answer, & (b) is not just about how to use tensorflow.

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Using `relu` as activation function for regression with only positive values

I'm building a deep learning model to predict times of arrival. By definition, the time of arrival is always positive. I'm wondering if I can use a relu as the ...
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Training batch size in relation to number of classes in a neural network

I'm using Keras on top of Theano for neural network training. What should be my batch size in relation to the number of classes? I have 560 classes and if I use a batch size more than 128, I can't ...
venuktan's user avatar
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Fine-tune: ways to determine how many layers to unfreeze

How to determine amount of layers I should unfreeze while fine-tuning deep learning model? Is there any sets of rules or I should just experiment?
A Arbitrage's user avatar
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correcting for extremely downsampled data: keras class_weight is hurting my model

I have an extremely imbalanced dataset (millions of times more negatives) for a binary classification NN model. I am aggressively downsampling solely for the purpose of making training time manageable,...
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A2C in TensorFlow 2 using model with two heads

I am implementing some of the basic reinforcement learning algorithms but ran into a problem with an online (one-step TD) A2C implementation where my reward seems to decrease over time instead of ...
Gregor's user avatar
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custom loss function to optimize payoff via binary decision

I have written a custom loss function that is supposed to optimize a payoff via a binary decision. However, the neural networks is struggling to convert, and I'm suspecting that there's something ...
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Transfer learning on faster rcnn and tensorflow

I am trying to do transfer learning to reuse a pretrained neural net. I got the tensorflow faster rcnn official example to work, and now i would like to reuse it to detect my own classes. This is the ...
Diego Raffo's user avatar
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Dropout causes overfitting

I am trying to experiment with dropout in 2 layer NN on notMNIST dataset using TensorFlow (assignment 3 in Google Deep Learning Course on Udacity). But adding dropout causes fall in test accuracy and ...
Nikita Lapkov's user avatar
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TensorFlow Deep MNIST for Experts tutorial: kernels seem to never learn anything

I'm following Google's TensorFlow Deep MNIST for Experts tutorial. Here is my code: http://pastebin.com/ePktssrn The networks seems to get close to 100% accuracy after about training 1000 steps, ...
Andrey's user avatar
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Multivariate regression in Tensorflow where dependent variables also depend on each other

Dear Stackoverflow community, I would like to understand how to implement a multivariate regression in Tensorflow, where all the dependent variables yn depend on both input variables xn as well as ...
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Designing an ML model for solving nonograms

The Problem I am trying to create a model to solve nonograms. I want to solve nonograms of any size $N\times N$ where $ \mathbb{N} \ni N\leq 10$. (but actualy I will be happy with a fixed size for ...
Ariel Yael's user avatar
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High resolution in style transfer

I'm investigating a bit about neural style transfer and its practical applications and I've encountered a major issue. Are there methods for high resolution style transfer? I mean, the original Gatys' ...
Josemafuen's user avatar
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What are good values for sample weights for UNet?

I'm trying to implement U-Net (https://arxiv.org/abs/1505.04597) from scratch using Keras. The thing about UNet apart from its architecture, is that it's using weight-maps from the input images in the ...
vassiliskrikonis's user avatar
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Application of Wavelet Transform and Differencing on Time Series Data (to denoise and remove seasonal adjustment and other trends)

I am working on an LSTM model to predict time series data (stock prices) and I would like an opinion whether to denoise my data or not before feeding it into the model. According to Investopedia, ...
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Which machine learning model could be used for the following?

I am an experienced programmer but very new to machine learning. I have a data set that consists of about 50,000 sets of 2,000 ordered values. All of the values are floats normalised to between 0 and ...
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Why Massive Random Spikes of Validation Loss?

My problem is to estimate the length of a straight line in an image, in pixel. My training size is 6000 images, validation is 1000 images. Each image has 200 x 200 pixels. My data is generated using ...
VHanded's user avatar
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How to reduce impact of false positive images in Tensorflow Object Detection Framework?

I am training a single object detector(for car) with Faster R-CNN with Inception v2 config file. I started with around 300 examples of images of the object with bounding boxes and trained that, got ...
Abhay's user avatar
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Recognition the same object from different views

I have 33 classes (33 different objects). I need to recognize the object from any view of the object. Like a packet of potato chips, the packet has different appearance from different view (as shown ...
batuman's user avatar
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How to write loss function for variational autoencoder?

So I've trying to follow various resources (Geron, Doersch, Altesaar, et al.) to construct a working loss function for my variational autoencoder but I'm finding that formulations either seem to work ...
Matt's user avatar
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input image size for deep learinng models

i have two set of images. One of size 120*60 and other of size 1022*81. Most of the deep learning models require size 224*224 or some other standard dimension as an input. Can i put these images ...
decipher's user avatar
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Is my weight matrix *learning* from all the steps in my LSTM?

I'm attempting to build an LSTM in Tensorflow to take in a series of amino acids (represented as Bitfields) and output a series of Torsion angles (4 numbers ranging from -1 to 1) for each amino acid ...
Oni's user avatar
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Choosing the 'best' epoch to stop the training of neural network. Top accuracy not improving, but average is

I'm familiar with concepts like early stopping, and detection of plateau and so on. Tensorflow CNN training has a possibility of saving only best model too, according to model's accuracy metric (for ...
silver_rocket's user avatar
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106 views

Why an agent can't learn on cheat data?

I want to train a FinRL model which will trade on an exchange using Ray Tune. I tried two different tune runs: with future data(you can find this code by "#Future data") and without. I ...
gendrelom's user avatar
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Strange behaviour of training accuracy and loss function

Firstly, I want to mention that I am not looking for suggestions to improve the training accuracy of my NN. The only purpose of this question is to know what might be causing the peculiar behaviour ...
Ranjan's user avatar
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Vertical Federated Learning

Lately I have been working (mostly reading) on Federated Learning and the one type of federation that looks suitable for my case is the Vertical Federated Learning. You can read about it here. Briefly,...
s510's user avatar
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Gradient exploding problem in a graph neural network

I have a gradient exploding problem which I couldn't solve after trying for several days. I implemented a custom message passing graph neural network in tensorflow which is used to predict a ...
Achintha Ihalage's user avatar
2 votes
1 answer
285 views

How to deal with negative rewards in policy gradient with crossentropy loss

In policy gradient reinforcement learning we can use a loss function of the form -log(P)*reward, where P is the probability of ...
Mastiff's user avatar
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Finding the best weights for sparse categorical cross entropy loss

In semantic segmentation and similar applications, sparse categorical cross entropy is often used as a loss function. Now it usually happens that samples are imbalanced. In my case, I have one class ...
Manuel Popp's user avatar
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375 views

Actionability from Tensorboard's weight histograms?

There are a few questions across the site about how to interpret the weight histograms. I understand what the histogram is showing, but: What exactly does it mean when the weights in a given layer ...
rodrigo-silveira's user avatar
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Implementing Multiclass Dice Loss Function

I am doing multi class segmentation using UNet. My output from the model is, ...
Hamza Yerlikaya's user avatar
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116 views

LSTM architecture for anomaly detection

I'm testing out different implementation of LSTM autoencoder on anomaly detection on 2D input. My question is not about the code itself but about understanding the underlying behavior of each network. ...
Yoan B. M.Sc's user avatar
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Machine-learning regression coefficients

Say I want to do supervised learning of response variable $y_k$ (continuous) and feature variables $(x_k, z_k, a_k, b_k)$ where $k$ is the sample index. Instead of learning the general form $$ y \sim ...
jChoi's user avatar
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Gamma Regression as the Last Layer of the Neural Network

My current task involves predicting data that follows a Gamma distribution. To avoid confusion of notations, in the following discussion, the p.d.f will be $$\mathbb{P}(y|\alpha, \beta)=\frac{\beta^\...
Jeff's user avatar
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865 views

Resize images before training object detection

I am training an object detector. I didn't resize my image before labeling because the of assumption that the model does this automatically to fit its input shape. ...
Mereb Hayl's user avatar
2 votes
1 answer
276 views

Masked Autoencoder MADE implementation in TensorFlow vs Pytorch

I am following the course CS294-158 [1] and got stuck with the first exercise that requests to implement the MADE paper (see here [2]). My implementation in TensorFlow [3] achieves results that are ...
mgbacher's user avatar
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1 answer
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Which is the error of a value corresponding to the maximum of a function?

This is my problem: I use data observed with MUSE (which is an astronomical instrument provides cubes, i.e. an image for each wavelength with a certain range, link ) to extract a measure of redshift. ...
Giuseppe Angora's user avatar
2 votes
0 answers
175 views

Interpretation of Tensor Flow CNN results with big dips in accuracy while training

I am trying to classify images using a CNN in tensor flow. I am doing 10 fold cross validation. At each fold, the training set is 900+ images and the validation set is 100 images. It is only two ...
fiacobelli's user avatar
2 votes
1 answer
800 views

MAP of Gaussian Process Classification in Tensorflow Probability

I'm attempting to implement Gaussian Process Classification learning in tensorflow-probability, but my estimator turns out to be very biased toward zero. As opposed ...
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299 views

How do I set up my hyper-parameter space for optimizing a convolutional neural network (using packages Skopt and Tensorflow)

I just finished building a 1D CNN using TensorFlow, and I want to optimize a variety of hyper-parameters using Scikit-Optimize (skopt) (although, I would be willing to use whatever optimization ...
Paul's user avatar
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A mistake in Tensorflow's documation?

Tensorflow's documentation gives an example for text generation using a RNN with eager execution. To the best of my understanding, this examples defines a simple RNN (with a GRU cell and a projection ...
Borbei's user avatar
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Computing average precision metric and cost function for object detection task using scikitLearn and Tensorflow

I have a Data set that contains 5 thousand pictures of my object of interest and 5 thousand pictures with out it. I trained a Convolutional Neural Network using Tensor Flow to detect the position of ...
Manuel Sebastian Rios's user avatar
2 votes
0 answers
172 views

Neural network training: going backward to go forward?

I am working on CNN models which are intended to predict a protein's structure from its amino acid sequence. I have a decently large data set, 750 protein structures containing over 100,000 amino ...
John L.'s user avatar
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372 views

How to select the regularization parameter between two losses?

In deep learning, the total loss commonly consists of a task-specific loss and a weight regularized loss: loss = loss_specific + lambda * reg_loss In my case (...
mining's user avatar
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220 views

How to retrain a model (Inception) with 'prioritised' images in certain classifications

I am new to machine learning, and have constructed a basic CNN classifier by retraining the last layer of the Inception v3 model with my own image set into two classifications. I did this in Python ...
Ashley's user avatar
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Discrepancy between categorical cross entropy and classification accuracy

I have a convolution neural network with random weights initialized and Trained to perform binary classification. I have 2000 images as training data and 2000 validation data. The problem I am trying ...
Akshata Bhat's user avatar
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0 answers
1k views

LSTM Weight Matrix Interpretation

Consider the following code in Keras for building a LSTM model. ...
Sandipan Bhattacharyya's user avatar
2 votes
0 answers
714 views

Implementing Keras image captioning example

I want to implement the image captioning example that https://keras.io/getting-started/sequential-model-guide/#examples has , for experimentation. Instead of using their mentioned convnet, I decided ...
harveyslash's user avatar
2 votes
1 answer
701 views

How to express Bayesian Network or Markov Random Field using deep learning

Bayesian Nework and Makov random field are instances of general probabilistic graphical model. Is it possible to express Bayesian Network or Markov Random Field using deep learning? or in general to ...
Tianchen's user avatar
2 votes
0 answers
671 views

Binary classification with CNN for soccer ball detection doesn't converge

I'm working on a project where I want to detect classic soccer balls in live camera pictures using a Convolutional Neural Network. My Network is built up as follows: ...
ArnoXf's user avatar
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0 answers
610 views

Combining categorical and continuous features in DNN

I am creating an application that can take as inputs, two numbers (1 or 0) as well as a class defining a binary operation (AND OR XOR etc) and training the network to preform the operation. Without ...
Nick Delben's user avatar

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