-
Hi!
Just wondering how the RNN could be mixed into the `ODEProblem`
In flux times, it seems a Recur layer need to be created. However there is already a `Recurrence` in Lux.jl
[Training of UDEs w…
-
related paper
|摘要|
|---|
|State-of-the-art approaches for semantic image segmentation are built on Convolutional Neural Networks (CNNs). The typical segmentation architecture is composed of (a) a…
-
Description
This project aims to build a speech recognition model that can convert spoken language (audio input) into written text. The model uses techniques from Natural Language Processing (NLP) an…
-
Pose a question about the one of the following possible readings: “[Dropout: A Simple Way to Prevent Neural Networks from Overfitting (Links to an external site.)](https://www.jmlr.org/papers/volume15…
-
-
Hi walker, I don't know if you will see this or not but I have some questions about brain.py.
def dense(X, units, params):
# Reshape the parameters from a flat array to a matrix of weights and…
-
Hi I'm trying this visualisation library and ran on a simple MNIST network.
I'm comparing activation maximisation used here from the the one described here: https://blog.keras.io/how-convolutional-…
-
Hi! I have a question on model_T and model_Y in DML/ORF. I notice that, by default, model_T and model_Y use Lasso in scikit-learn, while I'm thinking to handle the high-dimensional confounding factors…
-
As mentioned in #7, we would like to have a basic implementation of a Deep Neural Network. The design should be consistent with other major libraries and should have enough flexibility to add other ty…
-
I would expect this Python implementation to be quite a bit slower than `linalg.solve`. If this is the case, the applications of this would be to use it with custom operators, which PyTorch doesn't cu…