77 citations · 584 across the 84 of their papers we have counts for
4 papers · 2 filters
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression
Tong Teng, Jie Chen, Yehong Zhang +1
This paper presents a variational Bayesian kernel selection (VBKS) algorithm for sparse Gaussian process regression (SGPR) models. In contrast to existing GP kernel selection algor…
Inverse Reinforcement Learning with Missing Data
Tien Mai, Quoc Phong Nguyen, Kian Hsiang Low +1
We consider the problem of recovering an expert's reward function with inverse reinforcement learning (IRL) when there are missing/incomplete state-action pairs or observations in…
Implicit Posterior Variational Inference for Deep Gaussian Processes
Haibin Yu, Yizhou Chen, Zhongxiang Dai +2
A multi-layer deep Gaussian process (DGP) model is a hierarchical composition of GP models with a greater expressive power. Exact DGP inference is intractable, which has motivated…
GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection
Quoc Phong Nguyen, Kar Wai Lim, Dinil Mon Divakaran +2
This paper looks into the problem of detecting network anomalies by analyzing NetFlow records. While many previous works have used statistical models and machine learning technique…