52 bayesian-inference-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" positions in Australia
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Monash University
- Curtin University
- University of Adelaide
- University of Sydney
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- Australian National University
- Flinders University
- La Trobe University
- Queensland University of Technology
- The University of Queensland
- UNIVERSITY OF WESTERN AUSTRALIA
- University of New South Wales
- 2 more »
- « less
-
Field
-
In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
-
clinical trials to assess its ability to measure hydration state. This project would use data from WearOptimo’s hydration sensor and develop novel Bayesian methods to model hydration state. How can hydration
-
learning by using Bayesian learning principles. Among other things, Bayesian learning gives AI systems the ability to quantitatively express a degree of belief about a prediction or statement. By bridging
-
The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
-
plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
-
Australian National University | Canberra, Australian Capital Territory | Australia | about 24 hours ago
, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning
-
AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 20 days ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine
-
: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and
-
Advanced strongly typed languages like Haskell and emerging type systems like refinement types (as implemented in Liquid Haskell) offer strong guarantees about the correctness of programs. However, when type errors occur it can be difficult for programmers to understand their cause. Such...
-
will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how environmental factors and antifouling technologies