Quantitative dynamic models are widely used to study cellular signal processing. A critical step in modelling is the estimation of unknown model parameters from experimental data. As model sizes and ...

Bayesian optimization (BO) is an indispensable tool to optimize objective functions that either do not have known functional forms or are expensive to evaluate. Currently, optimal experimental design ...

Artificial intelligence (AI) is playing a huge role in heat rate optimization. In some cases, AI-driven models have analyzed operational data to recommend control settings that reduce heat rates by ...

Two papers on MoE-specific quantization algorithms accepted at a workshop held in conjunction with ICML 2026Recognition ...

Researchers at the University of Illinois Urbana-Champaign and the University of Virginia have developed a new model architecture that could lead to more robust AI systems with more powerful reasoning ...

Pruna AI, a European startup that has been working on compression algorithms for AI models, is making its optimization framework open source on Thursday. Pruna AI has been creating a framework that ...

Sedai, the self-driving cloud™, today launched AI Agent Optimization: the first platform that autonomously optimizes the cost ...

As enterprise AI adoption enters the multi-model era, cost efficiency, performance, reliability, and governance have become ...