Deep Learning
Grounding Spatio-Temporal Language with Transformers
Language is an interface to the outside world.
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI
Roman Beliy, Guy Gaziv, Assaf Hoogi, Francesca Strappini, Tal Golan, Michal Irani
Neural Information Processing Systems http://nips.cc/
Dancing to Music
Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu, Ting-Chun Wang, Yu-Ding Lu, Ming-Hsuan Yang, Jan Kautz
Neural Information Processing Systems http://nips.cc/
Embedding Symbolic Knowledge into Deep Networks
Xie Yaqi, Ziwei Xu, Kuldeep S Meel, Mohan Kankanhalli, Harold Soh
In this work, we aim to leverage prior symbolic knowledge to improve the performance of deep models.
A Closer Look at Accuracy vs. Robustness Y ao-Y uan Y ang
We explore combining dropout with robust training methods and obtain better generalization.
Neural Spline Flows
However, these models do not offer exact density evaluation, and can be difficult to train.
