9 citations · 11 across the 9 of their papers we have counts for
3 papers · 1 filter
Quasi-random Multi-Sample Inference for Large Language Models
Aditya Parashar, Aditya Vikram Singh, Avinash Amballa +2
Large language models (LLMs) are often equipped with multi-sample decoding strategies. An LLM implicitly defines an arithmetic code book, facilitating efficient and embarrassingly…
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
Jinlin Lai, Justin Domke, Daniel Sheldon
Bayesian reasoning in linear mixed-effects models (LMMs) is challenging and often requires advanced sampling techniques like Markov chain Monte Carlo (MCMC). A common approach is t…
Predictive variational inference: Learn the predictively optimal posterior distribution
Jinlin Lai, Antonio Linero, Yuling Yao
Vanilla variational inference finds an optimal approximation to the Bayesian posterior distribution, but even the exact Bayesian posterior is often not meaningful under model missp…