A5059359207- Bayesian Modeling and Causal Inference
- AI-based Problem Solving and Planning
- Data Mining Algorithms and Applications
- Anomaly Detection Techniques and Applications
- Data Quality and Management
- Artificial Intelligence in Games
- Data Management and Algorithms
- Logic, Reasoning, and Knowledge
- Reinforcement Learning in Robotics
- Evolutionary Game Theory and Cooperation
- Machine Learning and Algorithms
- Fault Detection and Control Systems
- Time Series Analysis and Forecasting
- Data Visualization and Analytics
- Sports Analytics and Performance
- Formal Methods in Verification
- Machine Learning and Data Classification
- Hungarian Social, Economic and Educational Studies
- Product Development and Customization
- Scheduling and Optimization Algorithms
- Machine Learning in Healthcare
- Artificial Intelligence in Healthcare
- Semantic Web and Ontologies
- Natural Language Processing Techniques
- Risk and Safety Analysis
Monash University
2015-2024
Avenir Health
2024
Monash University Malaysia
2022
Australian Regenerative Medicine Institute
1997-2021
Brown University
1993-2013
Science Oxford
2013
University of Oxford
1992-2013
University of Maryland, Baltimore
2009
University of California, San Diego
2009
University of California, Irvine
2009
Recent years have seen significant progress in improving both the efficiency and effectiveness of time series classification. However, because best solution is typically Nearest Neighbor algorithm with relatively expensive Dynamic Time Warping as distance measure, successful deployments on resource constrained devices remain elusive. Moreover, recent explosion interest wearable devices, which limited computational resources, has created a growing need for very efficient classification...
Background— Excessive proliferation of pulmonary artery smooth muscle cells (PASMCs) plays an important role in the development idiopathic arterial hypertension (IPAH), whereas a rise cytosolic Ca 2+ concentration triggers PASMC contraction and stimulates proliferation. Recently, we demonstrated that upregulation TRPC6 channel contributes to PASMCs isolated from IPAH patients. This study sought identify single-nucleotide polymorphisms (SNPs) gene promoter are associated with have functional...
The pore-forming α-subunit, Kv1.5, forms functional voltage-gated K + (Kv) channels in human pulmonary artery smooth muscle cells (PASMC) and plays an important role regulating membrane potential, vascular tone, PASMC proliferation apoptosis. Inhibited Kv channel expression function have been implicated from patients with idiopathic arterial hypertension (IPAH). Here, we report that overexpression of the Kv1.5 gene ( KCNA5) other cell lines produced a 15-pS single current large whole was...
Survival prediction and treatment selection in lung cancer care are characterised by high levels of uncertainty. Bayesian Networks (BNs), which naturally reason with uncertain domain knowledge, can be applied to aid experts providing personalised survival estimates recommendations. Based on the English Lung Cancer Database (LUCADA), we evaluate feasibility BNs for these two tasks, while comparing performances various causal discovery approaches uncover most feasible network structure from...
People interpret verbal expressions of probabilities (e.g. 'very likely') in different ways, yet words are commonly preferred to numbers when communicating uncertainty. Simply providing numerical translations alongside reports or text containing should encourage consistency, but these guidelines often ignored. In an online experiment with 924 participants, we compared four formats for presenting the used US Intelligence Community Directive (ICD) 203 see whether any could improve...
This is the Proceedings of Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, which was held Bellevue, WA, August 11-15, 2013
We describe the development of a monitoring system which uses sensor observation data about discrete events to construct dynamically probabilistic model world. This is Bayesian network incorporating temporal aspects, we call dynamic belief network; it used reason under uncertainty both causes and consequences being monitored. The basic construction data-driven. However process combines with externally provided information agents' behavior, knowledge already contained within model, control...
In many complex, real-world situations, problem solving and decision making require effective reasoning about causation uncertainty. However, human in these cases is prone to confusion error. Bayesian networks (BNs) are an artificial intelligence technology that models uncertain supporting probabilistic causal making. date, BN methodologies software significant upfront training, do not provide much guidance on the model building process, support collaboratively BNs. BARD (Bayesian...
Abstract Fog events occur at Melbourne Airport, Melbourne, Victoria, Australia, approximately 12 times each year. Unforecast are costly to the aviation industry, cause disruption, and a safety risk. Thus, there is need improve operational fog forecasting. However, difficult forecast because of complexity physical processes impact local geography weather elements. Bayesian networks (BNs) probabilistic reasoning tool widely used for prediction, diagnosis, risk assessment in range application...
Path planning problems involve computing or finding a collision free path between two positions. A special kind of is complete coverage planning, where robot sweeps all area space in an environment. There are different methods to cover the area; however, they not designed optimize process. This paper proposes novel method based on genetic algorithms. In order check viability this approach optimal tested virtual The simulation results confirm feasibility method.