deep learning

OF-MSRN: Optical Flow-Auxiliary Multi-Task Regression Network for Direct Quantitative Measurement, Segmentation and Motion Estimation AAAI 2020 On Correctness of Automatic Differentiation for Non-Differentiable Functions NeurIPS 2020 On Deep Unsupervised Active Learning IJCAI 2020 Online Learning in Contextual Bandits using Gated Linear Networks NeurIPS 2020 On Synthesis for Supervised Monaural Speech Separation in Time Domain Interspeech 2020 On the linearity of large non-linear models: when and why the tangent kernel is constant NeurIPS 2020 On the universality of deep learning NeurIPS 2020 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning ICML 2020 Optimizing Through Learned Errors for Accurate Sports Field Registration WACV 2020 Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation CVPR 2020 PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes AAAI 2020 PF-Net: Point Fractal Network for 3D Point Cloud Completion CVPR 2020 PFRL: Pose-Free Reinforcement Learning for 6D Pose Estimation CVPR 2020 Phonemer at WNUT-2020 Task 2: Sequence Classification Using COVID Twitter BERT and Bagging Ensemble Technique based on Plurality Voting EMNLP 2020 PipeSwitch: Fast Pipelined Context Switching for Deep Learning Applications OSDI 2020 Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning ICLR 2020 PLLay: Efficient Topological Layer based on Persistent Landscapes NeurIPS 2020 Point-of-Interest Oriented Question Answering with Joint Inference of Semantic Matching and Distance Correlation AACL 2020 Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods AAAI 2020 Predicting Propositional Satisfiability via End-to-End Learning AAAI 2020 Probabilistic Graphical Models with Neural Networks in InferPy PGM 2020 Probabilistic Regression for Visual Tracking CVPR 2020 Protecting Geolocation Privacy of Photo Collections AAAI 2020 Pruning Filter in Filter NeurIPS 2020 Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point NeurIPS 2020