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@@ -57,10 +57,13 @@ which is introduced after chainer v3. See [this issue](https://github.com/pfnet-
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*2: Saliency modules only work after chainer v5.
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*3: Chainer v6 is released and [ChainerX](https://chainer.org/announcement/2018/12/03/chainerx.html) is newly introduced.
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In order to support this new feature & API, we are going to break backward compatibility for chainer chemistry v0.6.0 release.
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In order to support this new feature & API, we broke backward compatibility for chainer chemistry v0.6.0 release.
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See [ChainerX Documentation](https://chainer.org/announcement/2018/12/03/chainerx.html) for details.
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*4: We are going to drop python 2.x support in the near future.
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*4: python 2.x support is dropped, following the same policy with `chainer` and `rdkit`.
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*5: As [announced in chainer blog](https://chainer.org/announcement/2019/12/05/released-v7.html),
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further development will be limited to only serious bug-fixes and maintenance.
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## Installation
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@@ -145,6 +148,8 @@ pull request and add the name of your project to this list:
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- BayesGrad: Explaining Predictions of Graph Convolutional Networks ([paper](https://arxiv.org/abs/1807.01985), [code](https://github.com/pfnet-research/bayesgrad))
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- Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks ([paper](https://arxiv.org/abs/1902.01020), [code](https://github.com/k-ishiguro/chainer-chemistry/tree/gwm_for_CC))
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- GraphNVP: An Invertible Flow Model for Generating Molecular Graphs ([paper](https://arxiv.org/abs/1905.11600), [code](https://github.com/pfnet-research/graph-nvp))
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- Graph Residual Flow for Molecular Graph Generation ([paper](https://arxiv.org/abs/1909.13521))
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