ICML 2024 "bayesian inference" Papers
9 papers found
Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
Luyang Fang, Yongkai Chen, Wenxuan Zhong et al.
ICML 2024poster
Diffusive Gibbs Sampling
Wenlin Chen, Mingtian Zhang, Brooks Paige et al.
ICML 2024poster
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective
Fabian Falck, Ziyu Wang, Christopher Holmes
ICML 2024poster
Kernel Semi-Implicit Variational Inference
Ziheng Cheng, Longlin Yu, Tianyu Xie et al.
ICML 2024poster
Listening to the noise: Blind Denoising with Gibbs Diffusion
David Heurtel-Depeiges, Charles Margossian, Ruben Ohana et al.
ICML 2024poster
Logistic Variational Bayes Revisited
Michael Komodromos, Marina Evangelou, Sarah Filippi
ICML 2024poster
Path-Guided Particle-based Sampling
Mingzhou Fan, Ruida Zhou, Chao Tian et al.
ICML 2024poster
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
Hyeong Kyu Choi, Sharon Li
ICML 2024oral
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models
Louis Sharrock, Jack Simons, Song Liu et al.
ICML 2024spotlight