Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design

3 March 2021

Papers citing "Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design"

10 / 10 papers shown

Title
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies from Simulated Nonparametric Functions Cen Li Marc Toussaint Barbara Rakitsch Christoph Zimmer OffRL 92 0 0 26 Jan 2025
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 106 0 0 20 Jan 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 44 2 0 03 Jan 2025
Bayesian Experimental Design via Contrastive Diffusions Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 26 0 0 15 Oct 2024
Deep Optimal Sensor Placement for Black Box Stochastic Simulations Paula Cordero-Encinar Tobias Schröder P. Yatsyshin Andrew Duncan 45 0 0 15 Oct 2024
Amortised Experimental Design and Parameter Estimation for User Models of Pointing Antti Keurulainen Isak Westerlund Oskar Keurulainen Andrew Howes 10 7 0 19 Jul 2023
Simulation-Based Parallel Training Lucas Meyer Alejandro Ribés Bruno Raffin AI4CE 21 2 0 08 Nov 2022
Active Exploration via Experiment Design in Markov Chains Mojmír Mutný Tadeusz Janik Andreas Krause 18 14 0 29 Jun 2022
Interventions, Where and How? Experimental Design for Causal Models at Scale P. Tigas Yashas Annadani Andrew Jesson Bernhard Schölkopf Y. Gal Stefan Bauer CML 24 48 0 03 Mar 2022
Sequential Bayesian experimental designs via reinforcement learning Hikaru Asano OffRL 8 0 0 14 Feb 2022