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 ## Papers
 ### 2019
 - <a name="todo"></a> Continual learning of context-dependent processing in neural networks (**Nature Machine Intelligence 2019**) [[paper](https://rdcu.be/bOaa3)] [[code](https://github.com/beijixiong3510/OWM)] 
-- <a name="todo"></a> Large Scale Incremental Learning (**CVPR2019**) [[paper](https://arxiv.org/abs/1905.13260)] 
-- <a name="todo"></a> Learning a Unified Classifier Incrementally via Rebalancing (**CVPR2019**) [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Hou_Learning_a_Unified_Classifier_Incrementally_via_Rebalancing_CVPR_2019_paper.pdf)] 
+- <a name="todo"></a> Large Scale Incremental Learning (**CVPR2019**) [[paper](https://arxiv.org/abs/1905.13260)] [[code](https://github.com/wuyuebupt/LargeScaleIncrementalLearning)]
+- <a name="todo"></a> Learning a Unified Classifier Incrementally via Rebalancing (**CVPR2019**) [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Hou_Learning_a_Unified_Classifier_Incrementally_via_Rebalancing_CVPR_2019_paper.pdf)] [[code](https://github.com/hshustc/CVPR19_Incremental_Learning)]
 - <a name="todo"></a> Learning Without Memorizing (**CVPR2019**) [[paper](https://arxiv.org/pdf/1811.08051.pdf)] 
 - <a name="todo"></a> Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning (**CVPR2019**) [[paper](https://arxiv.org/abs/1904.03137)] 
 - <a name="todo"></a> Task-Free Continual Learning (**CVPR2019**) [[paper](https://arxiv.org/pdf/1812.03596.pdf)]