| Tightening Bounds for Variational Inference by Revisiting Perturbation Theory | Sep 30, 2019 | Gaussian ProcessesStochastic Optimization | —Unverified | 0 |
| Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters | Sep 29, 2019 | BIG-bench Machine LearningTime Series | CodeCode Available | 0 |
| Weakly Supervised Energy-Based Learning for Action Segmentation | Sep 28, 2019 | Action SegmentationSegmentation | CodeCode Available | 0 |
| Attention Forcing for Sequence-to-sequence Model Training | Sep 26, 2019 | Machine Translationmodel | —Unverified | 0 |
| Probabilistic modeling the hidden layers of deep neural networks | Sep 25, 2019 | valid | —Unverified | 0 |
| Self-Supervised Policy Adaptation | Sep 25, 2019 | Representation LearningTranslation | —Unverified | 0 |
| Discriminability Distillation in Group Representation Learning | Sep 25, 2019 | Action RecognitionFace Recognition | —Unverified | 0 |
| GraphNVP: an Invertible Flow-based Model for Generating Molecular Graphs | Sep 25, 2019 | Graph GenerationMolecular Graph Generation | —Unverified | 0 |
| Approximate hedging with proportional transaction costs in stochastic volatility models with jumps | Sep 24, 2019 | valid | —Unverified | 0 |
| Simple and Almost Assumption-Free Out-of-Sample Bound for Random Feature Mapping | Sep 24, 2019 | valid | —Unverified | 0 |
