ptcn
Tensorflow (2.x) implementation of a Temporal Convolutional Network architecture, with a probabilistic twist.
This project indulges a couple of curiosities:
- Working with convolutional sequence-to-sequence models a la An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
- Adding a bayesian twist to the network a la Bayesian Segnet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding
This implementation has been inspired by other projects, including:
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Release files for ptcn 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ptcn-0.1.3.tar.gz | 3.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ptcn-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.5 kB
Release files / ptcn-0.1.3.tar.gz
| Download URL | ptcn-0.1.3.tar.gz |
|---|---|
| Size | 3.4 kB |
| Tags | Source |
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Release files / ptcn-0.1.3-py3-none-any.whl
| Download URL | ptcn-0.1.3-py3-none-any.whl |
|---|---|
| Size | 4.2 kB |
| Tags | Python 3 |
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