Tag: Variational Inference

Researchers have introduced a statistical model designed to predict disease from microbiome data pooled across many studies, addressing a persistent ...

A new conditional diffusion framework called CDJMP predicts multi-agent vehicle trajectories with state-of-the-art accuracy while cutting inference time to under ...

Researchers have developed an importance-sampling-based black box variational inference algorithm that reuses earlier simulation evaluations to cut the computational cost ...

A new hierarchical topic model, DF_sLNDA, replaces LDA's flat Dirichlet prior with nested Dirichlet distributions guided by BERT-derived semantic constraints, ...

A new nested multi-time-scale stochastic approximation method eliminates ratio-induced bias in likelihood-free parameter estimation, improving accuracy by up to two ...

Researchers have built a Bayesian liquid neural network that scores posture quality while quantifying its own uncertainty and abstaining from ...

A new computational framework unifies the analysis of sensory encoding, functional connectivity, and behavioral readout in two-photon calcium imaging data, ...

The world of machine learning and artificial intelligence has reached a remarkable milestone with the awarding of the prestigious BBVA ...