All Questions
Tagged with neural-network lstm
229
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Semantics Building In LSTM-Based Models - How does a LSTM is able to extract and represent long data using just one value (long-memory)
How does a LSTM is able to extract and represent long sequences with data while using just one value (long-memory / LM) to maintain all this information?
If multiple value were used, it could be ...
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1
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41
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How good are LSTMs in generalizing when learning curves?
I'm interested in the following scenario: I want to learn a mapping that maps a function to another function, i.e. I want to approximate a functional operator. If one is unfimiliar with operators one ...
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Temporal mismatch
I am building a predictive model to determine risk for a disease over the course of a hospital stay. I am using medical records from a hospital electronic medical record database. The predictions are ...
- 131
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Connecting Flatten layer to Dense layer
I'm struggling with my neural network.
In short, I need to recreate a model from anywhere on the internet, I've found a model that combines BiLSTM, LSTM and GRU. However, based on the error I got when ...
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90
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Questions about hidden states of bidirectional LSTMs
I read this in an article about bidirectional LSTM:
In bidirectional LSTM, each word corresponds to two hidden states, one
for each direction. Thus, we concatenate these two hidden states to
...
user159173
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63
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Which ML algorithm is suitable for a dataset that has seasonality and trend?
I have a small dataset from 2006 to 2023, I would like to predict monthly sales for the next year. This is my data:
I already tried Prophet and NeuralProphet, but unfortunately they don't work well ...
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92
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Anomaly Detection in Log Data using LSTM
Problem Overview:
I am currently working on a project involving anomaly detection in log data. The anomalies are defined by deviations from historical patterns. The log data has a simple structure: [...
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138
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Custom Loss Function Returns Graph Execution Error: Can not squeeze dim[0], expected a dimension of 1, got 32
I have built a loss function which adds time and frequency weighted averages and variances to the MSE:
...
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43
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LSTM Training Interpretation
I have an LSTM and have the following chart showing training validation performance by epoch:
Could someone explain? How can my validation performance be better than my training performance in ...
- 143
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3
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193
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What is the most optimal machine learning model/algorithm to create a hangman solver?
Want to create a hangman solver, So what is the best ml algorithm (lstm,reinforcement learning, or etc) to use?
Do suggest any other optimal technique if you know?
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137
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Backward propagation slower as epochs increase in pytorch
I'm trying to replicate TasNet paper using Pytorch Lightning, but the training time increases as the epochs increase (the first epoch takes 20 seconds, the fifth 2:30 minutes).
I've used PyTorch ...
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44
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LSTM for classification
I am new to neural networks and I want to use LSTM to classify the on/off state of devices based on power values. In my training dataset, I have power values, device one (0,1), and device 2 (0,1). 0 ...
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How can i understand multiple lstm cells by unrolling?
I do not Unterstand the concept of multiple units in lstm.
If i have an lstm layer with 64 cells, how would be the cells applied to each time step by unrolling.
My understanding is that each time step ...
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1
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39
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Confusion regarding what constitutes a feature in a LSTM?
I have a Time Series problem, where I am trying to predict a single output at time $t$, $y_t$, given the $2$ previous time steps; $X_{t-2}, X_{t-1}$.
Let's just look at one observation for simplicity.
...
- 139
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59
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LSTM can accept inputs of different shapes in some cases
I thought that with an LSTM you could use sequences of any length as input, but with shape fixed for each time step, but I encountered an anomalous behavior.
The following code gives the error that I ...
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