DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment
Design

DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design

7 December 2023

Stefan Bauer

Papers citing "DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design"

5 / 5 papers shown

Title
Efficient Data Selection for Training Genomic Perturbation Models G. Panagopoulos J. Lutzeyer Sofiane Ennadir Michalis Vazirgiannis Jun Pang 144 0 0 18 Mar 2025
SSL Framework for Causal Inconsistency between Structures and Representations Hang Chen Xinyu Yang Keqing Du Wenya Wang 52 2 0 03 Jan 2025
BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Yusuf Roohani Jian Vora Qian Huang Zach Steinhart Alex Marson Percy Liang J. Leskovec Percy Liang Jure Leskovec LLMAG LM&Ro 44 13 0 27 May 2024
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 270 9,136 0 06 Jun 2015