# Ben

**Programming Languages:**

Python, MATLAB

**Spoken Languages:**

English

**Content Feed**

已回答

Is LSTM and fully connected networks changing channels or neurons？

We use "channels" or C to refer to the feature dimension - in the case of LSTM, BiLSTM, GRU I think of the operation as a loop o...

Is LSTM and fully connected networks changing channels or neurons？

We use "channels" or C to refer to the feature dimension - in the case of LSTM, BiLSTM, GRU I think of the operation as a loop o...

2 months 前 | 0

| 已接受

已回答

Different network architectures between downloaded and script-created networks - Tutorial: 3-D Brain Tumor Segmentation Using Deep Learning

Do you mean the order as described by lgraph.Layers? I can see that. The order of lgraph.Layers is independent of the order the...

Different network architectures between downloaded and script-created networks - Tutorial: 3-D Brain Tumor Segmentation Using Deep Learning

Do you mean the order as described by lgraph.Layers? I can see that. The order of lgraph.Layers is independent of the order the...

2 months 前 | 1

| 已接受

已回答

Is there any documentation on how to build a transformer encoder from scratch in matlab?

You can use selfAttentionLayer to build the encoder from layers. The general structure of the intermediate encoder blocks is li...

Is there any documentation on how to build a transformer encoder from scratch in matlab?

You can use selfAttentionLayer to build the encoder from layers. The general structure of the intermediate encoder blocks is li...

2 months 前 | 3

已回答

Physical Informed Neural Network - Identify coefficient of loss function

Yes this is possible, you can make the coefficient into a dlarray and train it alongside the dlnetwork or other dlarray-s as in...

Physical Informed Neural Network - Identify coefficient of loss function

Yes this is possible, you can make the coefficient into a dlarray and train it alongside the dlnetwork or other dlarray-s as in...

2 months 前 | 0

已回答

Error in LSTM layer architecture

It looks like the issue is the data you pass to trainNetwork. When you swap the 2nd lstmLayer to have OutputMode="last" then the...

Error in LSTM layer architecture

It looks like the issue is the data you pass to trainNetwork. When you swap the 2nd lstmLayer to have OutputMode="last" then the...

2 months 前 | 0

已回答

need help to convert to a dlnetwork

The workflow for dlnetwork and trainnet would be something like the following: image = randi(255,[3,3,4]); % create network ...

need help to convert to a dlnetwork

The workflow for dlnetwork and trainnet would be something like the following: image = randi(255,[3,3,4]); % create network ...

2 months 前 | 0

| 已接受

已回答

LSTM Layer input size.

For sequenceInputLayer you don't need to specify the sequence length as a feature. So you would just need numFeatures = 5. For ...

LSTM Layer input size.

For sequenceInputLayer you don't need to specify the sequence length as a feature. So you would just need numFeatures = 5. For ...

2 months 前 | 0

| 已接受

已回答

Train VAE for RGB image generation

The error is stating that the VAE outputs Y and the training images T are different sizes when you try to compute the mean-squar...

Train VAE for RGB image generation

The error is stating that the VAE outputs Y and the training images T are different sizes when you try to compute the mean-squar...

5 months 前 | 0

已回答

How to use "imageInputLayer" instead of "sequenceInputLayer"?

Your imageInputLayer([12,1]) is specifying that your input data is "images" with height 12, width 1 and 1 channel/feature. I ex...

How to use "imageInputLayer" instead of "sequenceInputLayer"?

Your imageInputLayer([12,1]) is specifying that your input data is "images" with height 12, width 1 and 1 channel/feature. I ex...

5 months 前 | 0

已回答

How to create Custom Regression Output Layer with multiple inputs for training sequence-to-sequence LSTM model?

Unfortunately it's not possible to define a custom multi-input loss layer. The possible options are: If Y, X1 and X2 have comp...

How to create Custom Regression Output Layer with multiple inputs for training sequence-to-sequence LSTM model?

Unfortunately it's not possible to define a custom multi-input loss layer. The possible options are: If Y, X1 and X2 have comp...

5 months 前 | 0

| 已接受

已回答

Error for dlarray format, but why?

This error appears to be thrown if the inputWeights have the wrong size, e.g. you can take this example code from help lstm num...

Error for dlarray format, but why?

This error appears to be thrown if the inputWeights have the wrong size, e.g. you can take this example code from help lstm num...

5 months 前 | 0

已回答

Where can I find the detailed structure of the autoencoder network variable "net" obtained by the trainautoencoder function? The network structure diagram provided by the "vie

You can view the network by calling the network function: % Set up toy data and autoencoder t = linspace(0,2*pi,10).'; phi =...

Where can I find the detailed structure of the autoencoder network variable "net" obtained by the trainautoencoder function? The network structure diagram provided by the "vie

You can view the network by calling the network function: % Set up toy data and autoencoder t = linspace(0,2*pi,10).'; phi =...

5 months 前 | 0

| 已接受

已回答

Trouble adding input signals in Neural ODE training

Hi, What data do you have for your input signal ? If you can write a function for , e.g. , then the @(t,x,p) odeModel(t,x,p,u)...

Trouble adding input signals in Neural ODE training

Hi, What data do you have for your input signal ? If you can write a function for , e.g. , then the @(t,x,p) odeModel(t,x,p,u)...

9 months 前 | 0

已回答

How to prepare the training data for neural net with concatenationLayer, which accepts the combination of sequence inputs and normal inputs?

You are right that to use trainNetwork with a network that has multiple inputs you will need to use a datastore. There is docume...

How to prepare the training data for neural net with concatenationLayer, which accepts the combination of sequence inputs and normal inputs?

You are right that to use trainNetwork with a network that has multiple inputs you will need to use a datastore. There is docume...

9 months 前 | 0

已回答

Potential data dimension mismatch in lstm layer with output mode as 'sequence'?

The LSTM and Fully Connected Layer use the same weights and biases for all of the sequence elements. The LSTM works by using it'...

Potential data dimension mismatch in lstm layer with output mode as 'sequence'?

The LSTM and Fully Connected Layer use the same weights and biases for all of the sequence elements. The LSTM works by using it'...

9 months 前 | 0

已回答

Predict function returns concatenation error for a two-input Deep Neural Network

The "Format" functionLayer is re-labelling the input as "CSSB", and the inputs are "CB", so it's going to make the batch dimensi...

Predict function returns concatenation error for a two-input Deep Neural Network

The "Format" functionLayer is re-labelling the input as "CSSB", and the inputs are "CB", so it's going to make the batch dimensi...

9 months 前 | 0

已回答

Why doesn't concatLayer in Deep Learning Toolbox concatenate the 'T' dimension?

You can create a layer that concatenates on the T dimension with functionLayer sequenceCatLayer = functionLayer(@(x,y) cat(3,x,...

Why doesn't concatLayer in Deep Learning Toolbox concatenate the 'T' dimension?

You can create a layer that concatenates on the T dimension with functionLayer sequenceCatLayer = functionLayer(@(x,y) cat(3,x,...

9 months 前 | 1

| 已接受

已回答

i need to utilize fully of my GPUs during network training!

To use more of the GPU resource per iteration you can increase the minibatch size. I'll note that the LSTM layer you are adding...

i need to utilize fully of my GPUs during network training!

To use more of the GPU resource per iteration you can increase the minibatch size. I'll note that the LSTM layer you are adding...

9 months 前 | 0

已回答

add more options to gruLayer's GateActivationFunction

I would recommend implementing this extended GRU layer as a custom layer following this example: https://www.mathworks.com/help...

add more options to gruLayer's GateActivationFunction

I would recommend implementing this extended GRU layer as a custom layer following this example: https://www.mathworks.com/help...

9 months 前 | 0

已回答

Is it possible to apply upper and lower bounds to predictions in an LSTM?

I believe the default LSTM has outputs bounded in (-1,1) due to the activation functions used. In any case you can try using ac...

Is it possible to apply upper and lower bounds to predictions in an LSTM?

I believe the default LSTM has outputs bounded in (-1,1) due to the activation functions used. In any case you can try using ac...

9 months 前 | 0

已回答

Hi, how do I fix the error please? i would like to build model with both sequance and image input layers, thanks

Concatenation does not expand over dimensions, for example the following errors: x = rand(1,10); y = rand(1); cat(1,x,y) If ...

Hi, how do I fix the error please? i would like to build model with both sequance and image input layers, thanks

Concatenation does not expand over dimensions, for example the following errors: x = rand(1,10); y = rand(1); cat(1,x,y) If ...

9 months 前 | 0

已回答

Forecasting single variable time series data using LSTM

The XTrain, YTrain, XVal and YVal must all be cell arrays with size (Number of Observations) x 1, and where each entry XTrain{1}...

Forecasting single variable time series data using LSTM

The XTrain, YTrain, XVal and YVal must all be cell arrays with size (Number of Observations) x 1, and where each entry XTrain{1}...

9 months 前 | 1

已回答

How to create LSTM network of multiple dimension

It appears your data is in (Batch) x (Sequence) x (Features) format. For trainNetwork you need to represent you sequence data as...

How to create LSTM network of multiple dimension

It appears your data is in (Batch) x (Sequence) x (Features) format. For trainNetwork you need to represent you sequence data as...

9 months 前 | 0

已回答

How to apply physics informed neural networks on Matlab toolbox?

I'm not sure if this answers your question but you can take the network from this example, defined in the "Define Deep Learning ...

How to apply physics informed neural networks on Matlab toolbox?

I'm not sure if this answers your question but you can take the network from this example, defined in the "Define Deep Learning ...

10 months 前 | 2

已回答

Data pre-processing function in ANN model

Are you using the Deep Learning Toolbox tools such as DAGNetwork, dlnetwork, trainNetwork and/or custom training loops? In that ...

Data pre-processing function in ANN model

Are you using the Deep Learning Toolbox tools such as DAGNetwork, dlnetwork, trainNetwork and/or custom training loops? In that ...

12 months 前 | 0

| 已接受

已回答

can i implement lstm layer from scratch using matlab in sequence to sequence regression

Sure, I think the best way to do this would be with a custom layer, you can follow this example that implements a modified LSTM ...

can i implement lstm layer from scratch using matlab in sequence to sequence regression

Sure, I think the best way to do this would be with a custom layer, you can follow this example that implements a modified LSTM ...

12 months 前 | 1

已回答

Unable to resolve the name 'helper.downloadSCNNLaneDetection'.

I believe you need to do the following 1. clone or download https://github.com/matlab-deep-learning/pretrained-spatial-CNN into...

Unable to resolve the name 'helper.downloadSCNNLaneDetection'.

I believe you need to do the following 1. clone or download https://github.com/matlab-deep-learning/pretrained-spatial-CNN into...

12 months 前 | 0

已回答

Problem while usinge UNET

The response size is the size of the target data. I see this error when trying to train a regression network and the network's o...

Problem while usinge UNET

The response size is the size of the target data. I see this error when trying to train a regression network and the network's o...

12 months 前 | 0

已回答

How to resolve "Unable to determine if experiment is for classification or regression because setup function returned invalid outputs"?

I think the issue is that the 2nd returned output of BayesOptExperiment_setup2 needs to be the layer array or layerGraph object ...

How to resolve "Unable to determine if experiment is for classification or regression because setup function returned invalid outputs"?

I think the issue is that the 2nd returned output of BayesOptExperiment_setup2 needs to be the layer array or layerGraph object ...

12 months 前 | 0

已回答

Generate Text with Deep Learning "Invalid training data. Labels must not contain undefined values" ERROR

There are a few issues to fix this: The call to Y = categorical(charactersShifted) needs to include a valueset that includes al...

Generate Text with Deep Learning "Invalid training data. Labels must not contain undefined values" ERROR

There are a few issues to fix this: The call to Y = categorical(charactersShifted) needs to include a valueset that includes al...

1 year 前 | 1