dirichlet distribution

Learning Mixture of Neural Temporal Point Processes for Multi-dimensional Event Sequence Clustering IJCAI 2022 DrNAS: Dirichlet Neural Architecture Search ICLR 2021 Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? ICML 2021 Instance-Dependent Partial Label Learning NeurIPS 2021 Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound NeurIPS 2021 Realistic evaluation of transductive few-shot learning NeurIPS 2021 Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network ICML 2021 Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets NeurIPS 2021 Trusted Multi-View Classification ICLR 2021 Unsupervised Opinion Summarization with Content Planning AAAI 2021 The continuous categorical: a novel simplex-valued exponential family ICML 2020 Uncertainty Aware Semi-Supervised Learning on Graph Data NeurIPS 2020 A New Distribution on the Simplex with Auto-Encoding Applications NeurIPS 2019 Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration NeurIPS 2019 Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model JMLR 2019 Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation EMNLP 2019 Dirichlet Simplex Nest and Geometric Inference ICML 2019 Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness NeurIPS 2019 Safeguarded Dynamic Label Regression for Noisy Supervision AAAI 2019 Scalable Deep Generative Relational Model with High-Order Node Dependence NeurIPS 2019 Uncertainty on Asynchronous Time Event Prediction NeurIPS 2019 Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification NeurIPS 2018 Dirichlet belief networks for topic structure learning NeurIPS 2018 Evidential Deep Learning to Quantify Classification Uncertainty NeurIPS 2018 The Poisson Gamma Belief Network NeurIPS 2015