to-read

	A	B	C	D	E	F	G	H	I
1	paper	links	tags	date	recommended by	added by	sneak peek	votes	read
2	Wasserstein Adversarial Examples via Projected Sinkhorn Iterations	https://arxiv.org/abs/1902.07906	adversarial examples; sinkhorn	2019-03-28		Victor		1	FALSE
3	Multimodal Explanations: Justifying Decisions and Pointing to the Evidence	https://arxiv.org/abs/1802.08129	multi-modal; justifications	2019-02-28		Victor	https://youtu.be/mDVD13M2X94?t=5812	1	FALSE
4	Neural Ordinary Differential Equations	https://arxiv.org/abs/1806.07366				Adel		1	FALSE
5	Self-Normalizing Neural Networks (SELU)	https://arxiv.org/pdf/1706.02515.pdf				Adel		1	FALSE
6	Opening the black box of Deep Neural Networks via Information	https://arxiv.org/pdf/1703.00810.pdf						1	FALSE
7	ON THE INFORMATION BOTTLENECK THEORY OF DEEP LEARNING	https://openreview.net/pdf?id=ry_WPG-A-						1	TRUE
8	Efficient Neural Architecture Search via Parameter Sharing	https://arxiv.org/pdf/1802.03268.pdf						1	FALSE
9	Regularized Evolution for Image Classifier Architecture Search	https://arxiv.org/pdf/1802.01548.pdf						1	FALSE
10	DARTS: Differentiable Architecture Search	https://arxiv.org/pdf/1806.09055.pdf						1	FALSE
11	BSN: Boundary Sensitive Network for Temporal Action Proposal Generation	https://arxiv.org/pdf/1806.02964.pdf						1	FALSE
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