Differences
This shows you the differences between two versions of the page.
Both sides previous revision Previous revision | |||
learning_to_purpose [2018/10/10 11:36] admin |
learning_to_purpose [2018/11/08 08:42] (current) admin |
||
---|---|---|---|
Line 209: | Line 209: | ||
improvement in generating more | improvement in generating more | ||
human-like stories than SOTA systems. | human-like stories than SOTA systems. | ||
+ | |||
+ | |||
+ | https://arxiv.org/abs/1706.04008 Recurrent Inference Machines for Solving Inverse Problems | ||
+ | |||
+ | We establish this framework by abandoning the traditional separation between | ||
+ | model and inference. Instead, we propose to learn both components jointly without the need to define | ||
+ | their explicit functional form. This paradigm shift enables us to bridge the gap between the fields | ||
+ | of deep learning and inverse problems. A crucial and unique quality of RIMs are their ability to | ||
+ | generalize across tasks without the need to retrain. We convincingly demonstrate this feature in our | ||
+ | experiments as well as state of the art results on image denoising and super-resolution. |