Publications related to Bayesian network

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Colin Neil Jones, Bratislav Svetozarevic, Wenjie Xu

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Elsevier Sci Ltd2024

Gibbs sampling the posterior of neural networks

Lenka Zdeborová, Giovanni Piccioli, Emanuele Troiani

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Bristol2024

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

Laurent Valentin Jospin, Jesse Ray Murray Lahaye

Bayesian statistics is concerned with the integration of new information obtained through observations with prior knowledge, and accordingly, is often related to information theory (Jospin 2022). Recursive Bayesian estimation methods, such as Kalman Filter ...

2023

Robust Outlier Rejection for 3D Registration with Variational Bayes

Mathieu Salzmann, Jiancheng Yang, Zheng Dang, Zhen Wei, Haobo Jiang

Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier f ...

Los Alamitos2023

Causal inference with recurrent and competing events

Mats Julius Stensrud, Pal Christie Ryalen, Matias Janvin

Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports injuries in ath ...

SPRINGER2023

Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings

Fabio Nobile, Juan Pablo Madrigal Cianci

In this work, we present, analyze, and implement a class of multilevel Markov chain Monte Carlo(ML-MCMC) algorithms based on independent Metropolis--Hastings proposals for Bayesian inverse problems. In this context, the likelihood function involves solving ...

2023

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning

Alexandre Massoud Alahi, Yuejiang Liu

Recent years have seen a surge of interest in learning high-level causal representations from low-level image pairs under interventions. Yet, existing efforts are largely limited to simple synthetic settings that are far away from real-world problems. In t ...

2023

Bayesian Optimization for Chemical Reactions

Philippe Schwaller, Jeff Guo, Bojana Rankovic

Reaction optimization is challenging and traditionally delegated to domain experts who iteratively pro-pose increasingly optimal experiments. Problematically, the reaction landscape is complex and often requires hundreds of experiments to reach convergence ...

Bern2023

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Bayesian network

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Gibbs sampling the posterior of neural networks

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

Robust Outlier Rejection for 3D Registration with Variational Bayes

Causal inference with recurrent and competing events

Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning

Spatiotemporal wildfire modeling through point processes with moderate and extreme marks

Bayesian Optimization for Chemical Reactions

Graph Chatbot

Chat with Graph Search

Robust Outlier Rejection for 3D Registration with Variational Bayes

Gibbs sampling the posterior of neural networks

Bayesian Optimization for Chemical Reactions

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning

Causal inference with recurrent and competing events

Spatiotemporal wildfire modeling through point processes with moderate and extreme marks

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering