Active Experimental Design

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17 papers4 papers in the last four weeks, up 33% on the four weeks before. 0.0% of all new papers.

When Does Feedback Help? Auditing Learned Voltage-Clamp Experimental Design
Oct 20, 2026Rayan Nyaupane, Abhiram BhupatirajuActive Experimental Design Feedback Control
The University of Texas at Austin
Adjoint-Based Calibration and Optimal Control of Stochastic Multiscale Bioprocess Digital Twins
Oct 7, 2026Keilung Choy, Wei XieActive Experimental Design Digital Twins
Northeastern University
Experimental Experience Modeling for Autonomous Research
Sep 30, 2026Wenda Wei, Yingchen Zhang, Ruqing Zhang +3AI Agents for Scientific Discovery Active Experimental Design
State Key Laboratory of AI Safety · Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences +1
Optimal Design for Active Preference Learning with Biased LLM Judges
Sep 30, 2026Zhongman Du, Huiming Zhang, Haodong Zhu +1Pairwise Preference Learning LLM Alignment
Beihang University · Zhongguancun Academy · Hangzhou Innovation Institute of Beihang University
ALDER: Discovering the Laws of a World by Acting in It
Sep 27, 2026Teng Cao, Yu Deng, Quentin Delfosse +1Scientific Discovery Action-Conditioned World Models
Technische Universität Darmstadt · Intrinsic · CS Department, TU Darmstadt +2
Biology-in-the-loop: Amortized Adaptive Hit Discovery in CRISPR Screens
Sep 10, 2026Carl Edwards, Edward De Brouwer, Xiner Li +5Benchmark Design Active Experimental Design
Genentech, South San Francisco, CA, USA
Resolution-Aware Experimental Design under Partial Identifiability
Sep 3, 2026Sofianos Panagiotis FotiasPartial Identification Bayesian Experimental Design
National Technical University of Athens
Deep Adaptive Bayesian Screening
Jul 18, 2026Jade Lejeune Herman, Arno Strouwen, Johan A. K. Suykens +1Amortized Inference Adaptive Sampling
Mechatronics, Biostatistics and Sensors (MeBioS) · KU Leuven · Kasteelpark Arenberg 30, B-3001 Leuven (Heverlee) +3
The Approximation Ratio for the Risk of Myopic Bayesian Active Learning for Linear Regression
Jul 7, 2026Stephen MussmannActive Learning Linear Regression
School of Computer Science Georgia Institute of Technology
Compressing the Validation Bottleneck: An Agentic Self-Driving Lab for Scientific Discovery
Jul 5, 2026Kyunghoon Hur, Chihun LeeAI for Science Multifidelity Modeling
AX Research Division, Korea Electronics Technology Institute, Republic of Korea · Material Data Division, Korea Institute of Materials Science, Republic of Korea
LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs
May 21, 2026Sanchit Kabra, Nikhil Abhyankar, Saaketh Desai +2Scientific Discovery Scientific Hypothesis Generation
1Virginia Tech · 2Sandia National Laboratories
Spend Less, Fit Better: Budget-Efficient Scaling Law Fitting via Active Experiment Selection
Apr 24, 2026Sijie Li, Shanda Li, Haowei Lin +3Active Experimental Design Scaling Laws
Peking University · Carnegie Mellon University · Datadog
Adaptive Simulation Experiment for LLM Policy Optimization
Apr 9, 2026Mingjie Hu, Siyang Gao, Jian-qiang Hu +1Active Experimental Design Policy Optimization
School of Management, Fudan University · H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology · Department of Systems Engineering, City University of Hong Kong
ALMAB-DC: Active Learning, Multi-Armed Bandits, and Distributed Computing for Sequential Experimental Design and Black-Box Optimization
Mar 22, 2026Foo Hui-Mean, Yuan-chin I ChangSequential Experimental Design Active Experimental Design
Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
Observationally Informed Adaptive Causal Experimental Design
Mar 4, 2026Erdun Gao, Liang Zhang, Jake Fawkes +5Active Experimental Design Causal Inference
Australian Institute for Machine Learning, Adelaide University · Hong Kong University of Science and Technology (Guangzhou) · University College London +3
Correcting Boundary Bias and Observation Independence in Bayesian Experimental Design
Feb 2, 2026Sanna Jarl, Jens Sjölund, Jonathan J. S. Scragg +1Active Learning Adaptive Sampling
Department of Material Science & Engineering Uppsala University RISE · Department of Information Technology Uppsala University · RISE
Multidimensional Bayesian Active Machine Learning of Working Memory Task Performance
Oct 1, 2025Dom CP Marticorena, Chris Wissmann, Zeyu Lu +1Active Experimental Design Active Learning
Department of Biomedical Engineering, Washington University, 1 Brookings Drive, St. Louis, MO 63130 · Department of Computer Science and Engineering, Washington University, 1 Brookings Drive, St. Louis, MO 63130

Oct 20, 2026J/K move · Enter open · S save

When Does Feedback Help? Auditing Learned Voltage-Clamp Experimental Design

Rayan Nyaupane, Abhiram Bhupatiraju

The University of Texas at Austin

Active Experimental Design Feedback Control Policy Learning

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A learned scientific controller can outperform a misspecified planner without benefiting from feedback. We audit two synthetic voltage-clamp tasks with a training-selected fixed protocol, current masking, a Bayesian reference, and an excluded target. Five recurrent policies repeat one fixed protocol in all 1,200 off-grid rollouts; masking current changes no decision. In a crossed four-hypothesis task, a fixed diagnostic pulse is followed by one learned choice. Policies then use the first current, but tie a correctly specified Bayesian controller, and a fitted threshold reproduces the learned actions without being that controller. The excluded-target prediction gain is

4.6991\times10^{-6}

nats per sample. Feedback use and protocol quality are separate tests. These cases establish neither biological discovery nor general RL superiority.