8 citations · 16 across the 7 of their papers we have counts for
3 papers · 1 filter
Scaling of Capability and Efficiency at Inference Time in Large Reasoning Models
Moritz Laber, Zohair Shafi, Germans Savcisens +6
Capability and efficiency are two key dimensions of reasoning in large language models (LLMs). Capability refers to the ability to solve a given problem correctly, whereas efficien…
Disentangled Multi-Fidelity Deep Bayesian Active Learning
Dongxia Wu, Ruijia Niu, Matteo Chinazzi +2
To balance quality and cost, various domain areas of science and engineering run simulations at multiple levels of sophistication. Multi-fidelity active learning aims to learn a di…
Deep Bayesian Active Learning for Accelerating Stochastic Simulation
Dongxia Wu, Ruijia Niu, Matteo Chinazzi +3
Stochastic simulations such as large-scale, spatiotemporal, age-structured epidemic models are computationally expensive at fine-grained resolution. While deep surrogate models can…