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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Word2Vec models for irrelevant word order

I'm searching for a ready-to-use model, preferably in TensorFlow, that learns embeddings for words from a corpus, but without taking word order into account. So far I have a vocabulary of 8822 words ...
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526 views

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, ...
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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 ...
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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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1answer
42 views

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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190 views

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 ...
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0answers
1k views

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 ...
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192 views

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 ...
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484 views

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 ...
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999 views

LSTM Weight Matrix Interpretation

Consider the following code in Keras for building a LSTM model. ...
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940 views

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 ...
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19 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. ...
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1answer
21 views

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. ...
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41 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 ...
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118 views

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 ...
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1answer
111 views

How to feed multivariate spatio-temporal data into cnn?

After trying to find an example for quite a while, I finally came to ask my question here: What I have: I have a temporal sequence of 2d spatial data with 100 cells(or pixels) in longitude and 30 ...
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1answer
386 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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157 views

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 ...
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52 views

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 ...
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493 views

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 ...
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93 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 ...
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518 views

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 ...
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2answers
595 views

Convolutional neural network: why would training accuacy and well as validation accuracy fluctuate wildly?

I am training a convnet on a binary classification problem using medical images. I;m doing a preliminary evaluation of various shallow nets to get a sense of what the best hyperparameters are likely ...
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209 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 ...
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1k views

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 ...
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684 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 ...
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576 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 ...
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638 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: ...
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0answers
538 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 ...
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11 views

Accuracy in DNN

How does number of batch size and steps per epoch affects the accuracy of the model? Edit: Training and validation accuracy both. I trained a model using CNN where the accuracy is changing relatively ...
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1answer
28 views

Mismatching dimensions of input/output in the WaveNet model for text-to-speech generation?

I have been trying to understand the model of how speech generation works, particularly in WaveNet model by Google. I was referring to the original WaveNet paper and this implementation: I find the ...
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11 views

Tfp.sts unexpected wights prior behavior

I am trying to build a time series structural model and get the coefficients of the external factor. here is the structure of the model ...
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1answer
36 views

How to understand network neural network architecture from a research paper

Hello everyone I have the following architecture from the DELP-DAR research paper (https://www.sciencedirect.com/science/article/pii/S0167865519303216) and I dont really understand two things, first ...
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1answer
26 views

Combine ReLU with TanH is a good idea?

I have a CNN implementation for the Generator of a GAN, internally, the architecture is using ReLU for non-linearities, but at the output, the paper of the architecture specifies Tanh must be used. ...
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Is Determinism important for Hyperparameter Tuning?

When training the Model on GPU, different results are retrieved for the same hyperparameters. This effect can be shut down by using CPU or Tensorflow 2.1. with deterministic settings. The Post on ...
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How to build a sentence classifier with tensorflow, that has two sub bi-lstms one for sentence embedding and other for sentence classification?

I want to build a model that takes a document, creates sentence embedding for each sentence using a bi-LSTM, then use the sequence of sentences embedding as input to another bi-LSTM that outputs a ...
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1answer
43 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 ...
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45 views

WGAN-GP stability loss

I am training a Conditional WaveGAN (1D DCGAN for audio) using WGAN-GP whose generator is of an auotencoder architecture. The network is trained to take an audio input, compress it, then decompress it ...
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1answer
33 views

Low memory time series input for deep learning

Background I have some data that looks like this: ...
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0answers
53 views

How to maximize subset accuracy for multilabel multiclass image classification

I working on multi-label multi-class image classification. I am using TensorFlow. Currently I am using sigmoid on output layer with binary_crossentrpy. Model is ...
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0answers
30 views

How is convolution process done with 4D kernel?

Applying convolution with kernel of shape (1, 1, 4, 6)to a tensor of shape (2, 3, 2, 4) the result will be (2, 3, 2, 6). ...
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60 views

Tensorboard: Why does validation loss get evaluated after training loss stops?

When I monitor my model through Tensorboard, I notice that Tensorboard stops plotting the training loss but not the validation loss. Since the early stopping module, as I set it up below, is ...
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0answers
34 views

Tensorflow - simple multilayer perceptron not stabilizing around mean of normally distributed y-values

I'm building an FX trading model where I'm trying to predict the +/- movement of a currency pair 5 minutes into the future. I've had some promising results adapting the model as a classifier (i.e., ...
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1answer
27 views

Why do my training losses go up?

I am new to Machine Learning and Tensorflow. For one of my courses, I need to train an MLP for the xor gate. But my losses somehow go up each epoch, which confuses me and I must admit that I ran out ...
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0answers
39 views

autoencoding spiky time series - better loss function?

I am experimenting with convolutional autoencoders for time series. My first network architectures work quite well. However, the autoencoder has a tendency to soften the spikes in the time series. And ...
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0answers
309 views

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 ...
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0answers
40 views

Neural Network to discover an unknown number of patterns from a dataset of images?

I have a big set of images (>10.000), where there are similarities among them. I need to find a number/group of image patterns (eg, 5) that represent all images. As I do not know what patterns are, ...
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107 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 ...
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21 views

Reference for Inception-v2

Cross-posted from Data Science StackExchange. The "Rethinking" paper doesn't describe the actual implementation of the Inception-v3 model in Tensorflow: an accurate description is written in model....
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