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 ...
eLife

TopoMetry systematically learns and evaluates the latent geometry of single-cell data

A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...
IEEE

Characterizing Cloud-Native LLM Inference at Bytedance and Exposing Optimization Challenges and Opportunities for Future AI Accelerators

Abstract: As a major provider of LLM inference services, ByteDance has continuously explored diverse accelerator options to meet the rapidly growing inference demands of various heterogeneous LLM ...
GitHub

geo_inference_script.py

work_dir (str): The directory where the model and output files will be saved. mask_to_vec (bool): Whether to convert the output mask to vector format. mask_to_coco (bool): Whether to convert the ...