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Added TimeDistributed option #51

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Added TimeDistributed option #51

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14 changes: 13 additions & 1 deletion README.md
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Expand Up @@ -39,4 +39,16 @@ Includes cifar10 training example. Achieves ~86% accuracy using Resnet18 model.

Note that ResNet18 as implemented doesn't really seem appropriate for CIFAR-10 as the last two residual stages end up
as all 1x1 convolutions from downsampling (stride). This is worse for deeper versions. A smaller, modified ResNet-like
architecture achieves ~92% accuracy (see [gist](https://gist.github.com/JefferyRPrice/c1ecc3d67068c8d9b3120475baba1d7e)).
architecture achieves ~92% accuracy (see [gist](https://gist.github.com/JefferyRPrice/c1ecc3d67068c8d9b3120475baba1d7e)).

## Update: 2017-11-21

### TimeDistributed

Many CNN+LSTM architectures require a TimeDistributed version of CNNs, which are applied on time-distributed inputs as common filter weights, and then fed to an LSTM. Invoking the argument

```py
time_distributed=True
```

creates a TimeDistributed version of resnet. The input_shape must be in the form `(nb_time_steps, nb_rows, nb_cols, nb_channels)`.
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