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Hello, I'm a newbie in Machine Learning.
I constructe a neural network using `torch` and I want Variable serve as neural network inputs.
my code:
```
model = nn.gen_nn()
model.load_state_dict(t…
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### Team Name:
Pratjz
### Project Description:
In this project, we will use Quantum Neural Network along with classical layers to create Hybrid Neural network using Pennylane & Tensorflow &…
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### Description
Learned Sparse Vectors claim to combine the benefits of sparse (i.e. lexical) and dense (i.e. vector) representations
From https://en.wikipedia.org/wiki/Learned_sparse_retrieval:…
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## 0. Paper
@incollection{NIPS2014_5346,
title = {Sequence to Sequence Learning with Neural Networks},
author = {Sutskever, Ilya and Vinyals, Oriol and Le, Quoc V},
booktitle = {Advances in Neural…
a1da4 updated
4 years ago
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As we find more and more edge cases of the parameter framework the API has become increasingly awkward. For example, `DeepAutoencoder::convert_to_neural_network(std::shared_ptr output_layer, float64_t…
gf712 updated
4 years ago
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Hi,
I read your eBook on Machine Learning which very well explains everything about linear regression, neural networks etc. It's really helpful.
I however had a question on the neural network imp…
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[Show, attend and tell: Neural image caption generation with visual attention](http://proceedings.mlr.press/v37/xuc15.html)
Inspired by recent work in machine translation and object detection, we int…
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# Abstract
In recent years, the application of machine learning and deep learning to classical cryptanalysis is an active research field.
In this project, we perform quantum cryptanalysis that combi…
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Here are 10 approaches to implement adaptive noise reduction, ordered by complexity/effectiveness:
### 1. Enhanced Spectral Subtraction
- Track noise floor during silence periods
- Use overlappin…