Representation Learning

Learning Flexible Latent Representations via Encapsulated Variational Encoders AAAI 2019 Learning from brains how to regularize machines NeurIPS 2019 Learning Heterogeneous Spatial-Temporal Representation for Bike-Sharing Demand Prediction AAAI 2019 Learning Hierarchical Priors in VAEs NeurIPS 2019 Learning Invariant Representations with Kernel Warping AISTATS 2019 Learning Joint Reconstruction of Hands and Manipulated Objects CVPR 2019 Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling NeurIPS 2019 Learning Latent Trees with Stochastic Perturbations and Differentiable Dynamic Programming ACL 2019 Learning Local Descriptors With a CDF-Based Dynamic Soft Margin ICCV 2019 Learning nonlinear level sets for dimensionality reduction in function approximation NeurIPS 2019 Learning Not to Learn: Training Deep Neural Networks With Biased Data CVPR 2019 Learning Representations by Maximizing Mutual Information Across Views NeurIPS 2019 Learning Representations of Sets through Optimized Permutations ICLR 2019 Learning Semantic Representations for Novel Words: Leveraging Both Form and Context AAAI 2019 Learning Spatio-Temporal Representation With Local and Global Diffusion CVPR 2019 Learning to Adaptively Scale Recurrent Neural Networks AAAI 2019 Learning to combine Grammatical Error Corrections ACL 2019 Learning to Control the Fine-grained Sentiment for Story Ending Generation ACL 2019 Learning to Copy for Automatic Post-Editing EMNLP 2019 Learning to Explain: Answering Why-Questions via Rephrasing ACL 2019 Learning to Extract Flawless Slow Motion From Blurry Videos CVPR 2019 Learning to Generate Word- and Phrase-Embeddings for Efficient Phrase-Based Neural Machine Translation EMNLP 2019 Learning to Localize Objects with Noisy Labeled Instances AAAI 2019 Learning to Localize Through Compressed Binary Maps CVPR 2019 Learning to Order Graph Elements with Application to Multilingual Surface Realization EMNLP 2019