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### Deep Learning Simplified Repository (Proposing new issue)
:red_circle: **Project Title** : Backpropagation in Neural Networks
:red_circle: **Aim** : Backpropagation is a fundamental algorithm u…
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## Description and motivation
I'm trying to make inference with different timesteps on a neural network that's trained with Feedback Alignment from biotorch, however it is showing the same accuracy…
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### Feature description
Add LSTM Algorithm to Neural Network Algorithms
**Feature Description:**
I would like to propose adding an LSTM (Long Short-Term Memory) algorithm to the existing neural…
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Line 20 of algorithm 11 should be outside of the for loop that starts in line 8. Otherwise, the weights will be updated before all the gradients are computed.
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Mocha is really nice project and has backpropagation implemented for many different layer types and neurons. However what is the best way to interface it in way to obtain one large parameter vector? I…
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反向传播(backpropagation):计算cost function关于w和b的偏微分。
要想应用反向传播,cost function需要满足两个条件:
1. The cost function can be written as an average C=1/n*∑C_x over cost functions C_x for individual training examp…
hysic updated
7 years ago
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## Source
- [What is Gradient Descent?](https://www.linkedin.com/posts/shubhangi-sakarkar-66b049112_interview-question-what-is-gradient-descent-activity-7043436894596075520-rhgS/)
- [How Does the Gra…
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### 🚀 The feature, motivation and pitch
DTW is a crucial algorithm for measuring similarity between temporal sequences, but its computational complexity can be a bottleneck, particularly with large…
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Nice to see there's already an implementation of this!
I just stumbled across [tensorflow's "stop_gradient" function](https://www.tensorflow.org/api_docs/python/tf/stop_gradient). In the examples o…
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Hi, thanks for the implementation!
I hope to adopt your algorithm in a deep learning framework, which requires backpropagation in Pyotrch. Nevertheless, your algorithm is written in numpy. I suppo…