Papers
Uncertainty Guided Multi-Scale Residual Learning-Using a Cycle Spinning CNN for Single Image De-Raining
Rajeev Yasarla, Vishal M. Patel
Uncertainty Modeling of Contextual-Connections Between Tracklets for Unconstrained Video-Based Face Recognition
Jingxiao Zheng, Ruichi Yu, Jun-Cheng Chen et al.
Uncertainty on Asynchronous Time Event Prediction
Marin Biloš, Bertrand Charpentier, Stephan Günnemann
Unconstrained Foreground Object Search
Yinan Zhao, Brian Price, Scott Cohen et al.
Unconstrained Monotonic Neural Networks
Antoine Wehenkel, Gilles Louppe
Unconstrained Motion Deblurring for Dual-Lens Cameras
M. R. Mahesh Mohan, Sharath Girish, A. N. Rajagopalan
Uncoupled Regression from Pairwise Comparison Data
Liyuan Xu, Junya Honda, Gang Niu et al.
Uncovering Probabilistic Implications in Typological Knowledge Bases
Johannes Bjerva, Yova Kementchedjhieva, Ryan Cotterell et al.
Uncovering Specific-Shape Graph Anomalies in Attributed Graphs
Nannan Wu, Wenjun Wang, Feng Chen et al.
Uncover Sexual Harassment Patterns from Personal Stories by Joint Key Element Extraction and Categorization
Yingchi Liu, Quanzhi Li, Marika Cifor et al.
Uncover Sexual Harassment Patterns from Personal Stories by Joint Key Element Extraction and Categorization
Yingchi Liu, Quanzhi Li, Marika Cifor et al.
Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework
Junfan Chen, Richong Zhang, Yongyi Mao et al.
Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework
Junfan Chen, Richong Zhang, Yongyi Mao et al.
Underexposed Photo Enhancement Using Deep Illumination Estimation
Ruixing Wang, Qing Zhang, Chi-Wing Fu et al.
Understanding Actors and Evaluating Personae with Gaussian Embeddings
Hannah Kim, Denys Katerenchuk, Daniel Billet et al.
Understanding and Accelerating Particle-Based Variational Inference
Chang Liu, Jingwei Zhuo, Pengyu Cheng et al.
Understanding and Controlling Memory in Recurrent Neural Networks
Doron Haviv, Alexander Rivkind, Omri Barak
Understanding and correcting pathologies in the training of learned optimizers
Luke Metz, Niru Maheswaranathan, Jeremy Nixon et al.
Understanding and Improving Hidden Representations for Neural Machine Translation
Guanlin Li, Lemao Liu, Xintong Li et al.
Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer
David Berthelot*, Colin Raffel*, Aurko Roy et al.
Understanding and Improving Layer Normalization
Jingjing Xu, Xu Sun, Zhiyuan Zhang et al.
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Pengfei Chen, Ben Ben Liao, Guangyong Chen et al.
Understanding and Visualizing Deep Visual Saliency Models
Sen He, Hamed R. Tavakoli, Ali Borji et al.
Understanding and Visualizing Raw Waveform-Based CNNs
Hannah Muckenhirn, Vinayak Abrol, Mathew Magimai-Doss et al.
Understanding Attention and Generalization in Graph Neural Networks
Boris Knyazev, Graham W. Taylor, Mohamed Amer