Social interactions for autonomous driving: A review and perspectives
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …
their goals in social traffic scenes. A rational human driver can interact with other road users …
[PDF][PDF] Bayesian nonparametric hidden semi-Markov models
MJ Johnson, AS Willsky - 2013 - jmlr.org
There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-
HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov …
HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov …
Capturing and understanding workers' activities in far‐field surveillance videos with deep action recognition and Bayesian nonparametric learning
Recording workers' activities is an important, but burdensome, management task for site
supervisors. The last decade has seen a growing trend toward vision‐based activity …
supervisors. The last decade has seen a growing trend toward vision‐based activity …
Bayesian nonparametric inference of switching dynamic linear models
Many complex dynamical phenomena can be effectively modeled by a system that switches
among a set of conditionally linear dynamical modes. We consider two such models: the …
among a set of conditionally linear dynamical modes. We consider two such models: the …
Neuronal dynamics of the default mode network and anterior insular cortex: Intrinsic properties and modulation by salient stimuli
The default mode network (DMN) is critical for self-referential mental processes, and its
dysfunction is implicated in many neuropsychiatric disorders. However, the …
dysfunction is implicated in many neuropsychiatric disorders. However, the …
A survey on Bayesian nonparametric learning
Bayesian (machine) learning has been playing a significant role in machine learning for a
long time due to its particular ability to embrace uncertainty, encode prior knowledge, and …
long time due to its particular ability to embrace uncertainty, encode prior knowledge, and …
Learning movement primitive libraries through probabilistic segmentation
Movement primitives are a well-established approach for encoding and executing
movements. While the primitives themselves have been extensively researched, the concept …
movements. While the primitives themselves have been extensively researched, the concept …
Statistical anomaly detection in human dynamics monitoring using a hierarchical dirichlet process hidden markov model
T Fuse, K Kamiya - IEEE Transactions on Intelligent …, 2017 - ieeexplore.ieee.org
Understanding of human dynamics has drawn attention to various areas. The wide spread of
positioning technologies, such as GPS facilitates location information to be obtained with …
positioning technologies, such as GPS facilitates location information to be obtained with …
[HTML][HTML] Predicting intervention onset in the ICU with switching state space models
The impact of many intensive care unit interventions has not been fully quantified, especially
in heterogeneous patient populations. We train unsupervised switching state autoregressive …
in heterogeneous patient populations. We train unsupervised switching state autoregressive …
[BOOK][B] Hidden Semi-Markov models: theory, algorithms and applications
SZ Yu - 2015 - books.google.com
Hidden semi-Markov models (HSMMs) are among the most important models in the area of
artificial intelligence/machine learning. Since the first HSMM was introduced in 1980 for …
artificial intelligence/machine learning. Since the first HSMM was introduced in 1980 for …