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Embedding Logical Queries on Knowledge Graphs
Will Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec
Learning low-dimensional embeddings of knowledge graphs is a powerful approach used to predict unobserved or missing edges between entities.
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee
Neural Information Processing Systems http://nips.cc/
On Adversarial Mixup Resynthesis
Christopher Beckham, Sina Honari, Vikas Verma, Alex M. Lamb, Farnoosh Ghadiri, R Devon Hjelm, Yoshua Bengio, Chris Pal
Neural Information Processing Systems http://nips.cc/
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks
Anirvan Sengupta, Cengiz Pehlevan, Mariano Tepper, Alexander Genkin, Dmitri Chklovskii
Neural Information Processing Systems http://nips.cc/
Adaptive Influence Maximization with Myopic Feedback
Neural Information Processing Systems http://nips.cc/
Video Prediction via Selective Sampling
Jingwei Xu, Bingbing Ni, Xiaokang Yang
This module is trained in an adversarial learning manner [5]. The Selectionmodule selects high possibility candidates from proposals and combines to produce the final prediction, according to the criteria of better position matching.