Variational Bayesian optimal experimental design

Variational Bayesian optimal experimental design

Bayesian optimal experimental design (BOED) is a principled framework for making efficient use of limited experimental resources. Unfortunately, its applicability is hampered by the difficulty of obtaining accurate estimates of the expected information gain (EIG) of an experiment. To address this, w...

Disgrifiad llawn

Manylion Llyfryddiaeth
Prif Awduron:	Foster, A, Jankowiak, M, Bingham, E, Horsfall, P, Tee, YW, Rainforth, T, Goodman, N
Fformat:	Conference item
Cyhoeddwyd:	Conference on Neural Information Processing Systems 2019

Eitemau Tebyg

A unified stochastic gradient approach to designing Bayesian-optimal experiments
gan: Foster, A, et al.
Cyhoeddwyd: (2020)

Modern Bayesian experimental design
gan: Rainforth, T, et al.
Cyhoeddwyd: (2024)

Variational, Monte Carlo and policy-based approaches to Bayesian experimental design
gan: Foster, AE
Cyhoeddwyd: (2021)

Making better use of unlabelled data in Bayesian Active learning
gan: Bickford Smith, F, et al.
Cyhoeddwyd: (2024)

Bayesian Optimization for Probabilistic Programs
gan: Rainforth, T, et al.
Cyhoeddwyd: (2016)

Target–aware Bayesian inference: how to beat optimal conventional estimators
gan: Rainforth, T, et al.
Cyhoeddwyd: (2020)

Optimal Bayesian experimental design in the presence of model error
gan: Feng, Chi, S.M. Massachusetts Institute of Technology
Cyhoeddwyd: (2015)

SelfCheck: using LLMs to zero-shot check their own step-by-step reasoning
gan: Miao, N, et al.
Cyhoeddwyd: (2024)

Numerical approaches for sequential Bayesian optimal experimental design
gan: Huan, Xun
Cyhoeddwyd: (2016)

Bayesian Optimization for Adaptive Experimental Design: A Review
gan: Stewart Greenhill, et al.
Cyhoeddwyd: (2020-01-01)

Beyond Bayesian model averaging over paths in probabilistic programs with stochastic support
gan: Reichelt, T, et al.
Cyhoeddwyd: (2024)

Simulation-based optimal Bayesian experimental design for nonlinear systems
gan: Huan, Xun, et al.
Cyhoeddwyd: (2015)

GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN
gan: Huan, Xun, et al.
Cyhoeddwyd: (2015)

Bayesian optimization with known experimental and design constraints for chemistry applications
gan: Hase, Florian
Cyhoeddwyd: (2022)

Bayesian optimization with adaptive surrogate models for automated experimental design
gan: Bowen Lei, et al.
Cyhoeddwyd: (2021-12-01)

A combinatorial approach to goal-oriented optimal Bayesian experimental design
gan: Li, Fengyi,S.M.Massachusetts Institute of Technology.
Cyhoeddwyd: (2019)

Disentangling disentanglement in variational autoencoders
gan: Mathieu, E, et al.
Cyhoeddwyd: (2019)

Output-Weighted Optimal Sampling for Bayesian Experimental Design and Uncertainty Quantification
gan: Blanchard, Antoine, et al.
Cyhoeddwyd: (2022)

Bayesian Optimal Experimental Design for Race Tracking in Resin Transfer Moulding
gan: Nicholas Wright, et al.
Cyhoeddwyd: (2023-10-01)

Automating inference, learning, and design using probabilistic programming
gan: Rainforth, T
Cyhoeddwyd: (2017)

Fully Bayesian Experimental Design for Pharmacokinetic Studies
gan: Elizabeth G. Ryan, et al.
Cyhoeddwyd: (2015-03-01)

SMC Samplers for Bayesian Optimal Nonlinear Design
gan: Kuck, H, et al.
Cyhoeddwyd: (2006)

Divide, conquer, and combine: a new inference strategy for probabilistic programs with stochastic support
gan: Zhou, Y, et al.
Cyhoeddwyd: (2020)

SMC samplers for Bayesian optimal nonlinear design
gan: Kueck, H, et al.
Cyhoeddwyd: (2006)

An Iterative Nonlinear Filter Using Variational Bayesian Optimization
gan: Yumei Hu, et al.
Cyhoeddwyd: (2018-12-01)

Online variational filtering and parameter learning
gan: Campbell, A, et al.
Cyhoeddwyd: (2022)

Accounting for Computational Expenditures in Bayesian Experimental Design
gan: Zheng, Sue
Cyhoeddwyd: (2022)

Opening Design using Bayesian Optimization
gan: Nick Vitsas, et al.
Cyhoeddwyd: (2023-12-01)

Towards a theoretical understanding of the robustness of variational autoencoders
gan: Camuto, A, et al.
Cyhoeddwyd: (2021)

Meta-analysis of the experimental coefficient of variation in wheat using the Bayesian and Frequentist approaches
gan: Maicon Nardino, et al.
Cyhoeddwyd: (2022-06-01)

A Bayesian interactive optimization approach to procedural animation design
gan: Brochu, E, et al.
Cyhoeddwyd: (2010)

Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach
gan: Arpan Biswas, et al.
Cyhoeddwyd: (2023-01-01)

Automation of Experimental Modal Analysis Using Bayesian Optimization
gan: Johannes Ellinger, et al.
Cyhoeddwyd: (2023-01-01)

Integrating a tailored recurrent neural network with Bayesian experimental design to optimize microbial community functions.
gan: Jaron C Thompson, et al.
Cyhoeddwyd: (2023-09-01)

Integrating a tailored recurrent neural network with Bayesian experimental design to optimize microbial community functions
gan: Jaron C. Thompson, et al.
Cyhoeddwyd: (2023-09-01)

Optimal experiment design with adjoint-accelerated Bayesian inference
gan: Matthew Yoko, et al.
Cyhoeddwyd: (2024-01-01)

Accelerated Bayesian experimental design for chemical kinetic models
gan: Huan, Xun
Cyhoeddwyd: (2010)

Bayesian Inference and Experimental Design of Combustion Kinetic Models
gan: Chen, Huaibo
Cyhoeddwyd: (2024)

Automated data acquisition via Bayesian experimental design
gan: Ivanova, DR
Cyhoeddwyd: (2024)

Bayesian experimental design and parameter estimation for ultrafast spin dynamics
gan: Zhantao Chen, et al.
Cyhoeddwyd: (2023-01-01)