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Delves into Bayesian Knowledge Tracing and Learning Curves, exploring the prediction of student knowledge over time and the importance of accurate performance measurement.
Explores Variational Auto-Encoders, Bayesian inference, attention-based latent spaces, and the effectiveness of Transformers in language processing.
Explores theorem proving in first-order logic and the saturation-based approach, highlighting the Vampire theorem prover.
Explores knowledge inference for graphs, discussing label propagation, optimization objectives, and probabilistic behavior.
Focuses on the inference of reaction kinetics in combustion, covering rules inference, sensitivity analysis, and Bayesian inference.
Explores high-resolution Bayesian mapping of landslide hazard, emphasizing the significance of capturing unobserved triggers like rainfall intensity.
