"bayesian inference" Papers

15 papers found

Consensus-Driven Active Model Selection

Justin Kay, Grant Horn, Subhransu Maji et al.

ICCV 2025highlightarXiv:2507.23771
2
citations

Model-Informed Flows for Bayesian Inference

Joohwan Ko, Justin Domke

NeurIPS 2025posterarXiv:2505.24243

Modeling Neural Activity with Conditionally Linear Dynamical Systems

Victor Geadah, Amin Nejatbakhsh, David Lipshutz et al.

NeurIPS 2025oralarXiv:2502.18347

Parallelizing MCMC Across the Sequence Length

David Zoltowski, Skyler Wu, Xavier Gonzalez et al.

NeurIPS 2025posterarXiv:2508.18413
3
citations

Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation

Ting Wei, Biao Mei, Junliang Lyu et al.

NeurIPS 2025posterarXiv:2505.14161
1
citations

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

Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model

Shunsuke Horii, Yoichi Chikahara

AAAI 2024paperarXiv:2312.10435
6
citations