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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months 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
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months 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
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-GRASP”, “Simulation-Based Bayesian Inference for Object Perception in Robot Grasping”, financed by the European Union´s Horizon Europe research & innovation programme under the euROBIN project (Grant
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of current issues and future directions within the field of Active Inference, control theory or Bayesian inference. B7 Experience with building computational models of human users in an interaction setting. B8
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the timing, scale, and rate of mammal declines in Australia. They will use critical inferences of past demographic change and high-performance computing to disentangle the ecological mechanisms that were