电子与信息学报投稿：一种可解释的自由文本击键事件序列分类模型. An Interpretable Free-text Keystroke Event Sequence Classification Model.
Implementations of Gaussian Process Regression Hyper-Parameter Optimization Using Cross-Validation and Non-linearly Constrained ADMM
A Python implementation of global optimization with gaussian processes.
A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.
implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
Modeling the asynchronous event sequence via Recurrent Point Process
# Using variational Bayes for point processes to analyze CMU dataset. Modify the project created by https://github.com/st--/vbpp, to analyze CMU dataset(http://www.cs.cmu.edu/~keystroke/DSL-StrongPasswordData.xls).
An implementation of the model described in "Efficient Inference in Multi-task Cox Process Models".
Scalable hyperparameter tuning in probabilistic knowledge graph embedding models (Bamler, Salehi, and Mandt, UAI 2019)
