BBC

What is inference?

When we read stories, watch films or TV shows, look at pictures or play video games, we use lots of different skills to work out what is happening. One of these skills is called inference. Inferring ...
IEEE

Federated Experiments: Generative Causal Inference Powered by LLM-Based Agents Simulation and RAG-Based Domain Docking

Abstract: Computational experiments method is an essential tool for analyzing, designing, managing, and integrating complex systems. However, a significant challenge arises in constructing agents with ...
Scientific Research Publishing

Determinants of Supply Chain Resilience of Operating Theatre Supplies in Lusaka District, Zambia: The Role of Demand Forecasting and Lead-Time Management ()

Background: Ensuring the consistent availability of operating theatre supplies is critical for safe surgical care. However, supply chain disruptions remain common in low ...
Frontiers

Causal AI: Integrating Causality and Machine Learning for Robust Intelligent Systems

Artificial Intelligence (AI) has achieved remarkable success across domains including healthcare, finance, climate modelling, and autonomous systems. However, the dominant paradigms in AI, ...
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 ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
GitHub

inference-performance-field-manual.html

.toc-pill.frame { background: var(--rust); color: var(--paper); border-color: var(--rust); } .toc-pill.bench { background: var(--gold); color: var(--ink); border ...
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.