Bayesian Inference

The Stanford Acuity Test: A Precise Vision Test Using Bayesian Techniques and a Discovery in Human Visual Response AAAI 2020 Thompson Sampling for Adversarial Bit Prediction ALT 2020 Thompson Sampling for Unsupervised Sequential Selection ACML 2020 Thompson Sampling via Local Uncertainty ICML 2020 To Avoid the Pitfall of Missing Labels in Feature Selection: A Generative Model Gives the Answer AAAI 2020 Towards a Hierarchical Bayesian Model of Multi-View Anomaly Detection IJCAI 2020 Towards Scalable Bayesian Learning of Causal DAGs NeurIPS 2020 Training Binary Neural Networks using the Bayesian Learning Rule ICML 2020 Tree-Structured Neural Topic Model ACL 2020 TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources AAAI 2020 Tuning Causal Discovery Algorithms PGM 2020 Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly JMLR 2020 Tweedie-Hawkes Processes: Interpreting the Phenomena of Outbreaks AAAI 2020 Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End CVPR 2020 Uncertainty-Aware Deep Classifiers Using Generative Models AAAI 2020 Uncertainty-Aware Label Refinement for Sequence Labeling EMNLP 2020 Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation NeurIPS 2020 Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification AAAI 2020 Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization AAAI 2020 Uncertainty-aware Self-training for Few-shot Text Classification NeurIPS 2020 Uncertainty Aware Semi-Supervised Learning on Graph Data NeurIPS 2020 Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving WACV 2020 Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation MIDL 2020 Uncertainty-guided Continual Learning with Bayesian Neural Networks ICLR 2020 Uncertainty in Model-Agnostic Meta-Learning using Variational Inference WACV 2020