GitHub

deepgp_variational_inference_tutorial.py

from scratch in PyTorch. self-contained: no GPflow/GPyTorch. model: y = f_L(...f_2(f_1(x))) + eps, each f_l a sparse GP. inference: sample-through-the-layers variational inference.
IEEE

Variational Bayesian Inference-Based Method for Antenna Array Diagnosis

Abstract: Sparse diagnosis techniques for antenna arrays provide an efficient approach to fault diagnosis by leveraging the sparse nature of faulty elements. In practical scenarios, an unknown ...
IEEE

Inventory Probabilistic Forecasting Model for Demand Uncertainty: A Variational Poisson Inference Approach Based on Clustering and Deep Learning

Abstract: Due to the significant uncertainty in consumer demand for goods, inventory demand exhibits randomness and temporal heterogeneity, making it extremely difficult to summarize demand patterns ...
GitHub

Tutorial_NCM_v1.md

The quick way: read depth profiling and inference result visualization The depth_profile_ncm function provides a convenient way to run all three NCM inference methods across a range of rarefied read ...