4 citations · 8 across the 6 of their papers we have counts for
12 papers
Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with Explainability
Anubhab Ghosh, Antoine Honoré, Dong Liu +2
In pursuit of explainability, we develop generative models for sequential data. The proposed models provide state-of-the-art classification results and robust performance for speec…
Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows
Anubhab Ghosh, Antoine Honoré, Dong Liu +2
We test the robustness of a maximum-likelihood (ML) based classifier where sequential data as observation is corrupted by noise. The hypothesis is that a generative model, that com…
A Game Theoretic Analysis of LQG Control under Adversarial Attack
Zuxing Li, György Dán, Dong Liu
Motivated by recent works addressing adversarial attacks on deep reinforcement learning, a deception attack on linear quadratic Gaussian control is studied in this paper. In the co…
Belief Propagation for Approximate Inference
Dong Liu, Minh Thành Vu, Zuxing Li +1
Belief propagation (BP) algorithm is a widely used message-passing method for inference in graphical models. BP on loop-free graphs converges in linear time. But for graphs with lo…
Region-based Energy Neural Network for Approximate Inference
Dong Liu, Ragnar Thobaben, Lars K. Rasmussen
Region-based free energy was originally proposed for generalized belief propagation (GBP) to improve loopy belief propagation (loopy BP). In this paper, we propose a neural network…
On Dominant Interference in Random Networks and Communication Reliability
Dong Liu, Baptiste Cavarec, Lars K. Rasmussen +1
In this paper, we study the characteristics of dominant interference power with directional reception in a random network modelled by a Poisson Point Process. Additionally, the Lap…