Papers Experimental Design
“Experimental Design” 태그가 달린 논문 688편 · 필터 해제
Goal-Oriented Sequential Bayesian Experimental Design for Causal Learning
We present GO-CBED, a goal-oriented Bayesian framework for sequential causal experimental design. Unlike conventional approaches that select interventions aimed at inferring the full causal model, GO-CBED directly maximi…
Experimental DesignOptimal Design of Experiment for Electrochemical Parameter Identification of Li-ion Battery via Deep Reinforcement Learning
Accurate parameter estimation in electrochemical battery models is essential for monitoring and assessing the performance of lithium-ion batteries (LiBs). This paper presents a novel approach that combines deep reinforce…
Deep Reinforcement LearningExperimental DesignModel Predictive Controlparameter estimationExperimental Design for Semiparametric Bandits
We study finite-armed semiparametric bandits, where each arm's reward combines a linear component with an unknown, potentially adversarial shift. This model strictly generalizes classical linear bandits and reflects comp…
Experimental DesignOptimal experiment design for practical parameter identifiability and model discrimination
Mechanistic mathematical models of biological systems usually contain a number of unknown parameters whose values need to be estimated from available experimental data in order for the models to be validated and used to …
Experimental DesignEfficient Preference-Based Reinforcement Learning: Randomized Exploration Meets Experimental Design
We study reinforcement learning from human feedback in general Markov decision processes, where agents learn from trajectory-level preference comparisons. A central challenge in this setting is to design algorithms that …
Experimental Designreinforcement-learningReinforcement LearningComment on The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
Shojaee et al. (2025) report that Large Reasoning Models (LRMs) exhibit "accuracy collapse" on planning puzzles beyond certain complexity thresholds. We demonstrate that their findings primarily reflect experimental desi…
Experimental DesignGeneralization Analysis for Bayesian Optimal Experiment Design under Model Misspecification
In many settings in science and industry, such as drug discovery and clinical trials, a central challenge is designing experiments under time and budget constraints. Bayesian Optimal Experimental Design (BOED) is a parad…
Drug DiscoveryExperimental DesignALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
Many critical applications, from autonomous scientific discovery to personalized medicine, demand systems that can both strategically acquire the most informative data and instantaneously perform inference based upon it.…
Active LearningBayesian InferenceExperimental Designscientific discoveryImproved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards
We study stochastic linear bandits with heavy-tailed rewards, where the rewards have a finite $(1+\epsilon)$-absolute central moment bounded by $\upsilon$ for some $\epsilon \in (0,1]$. We improve both upper and lower bo…
Experimental DesignMulti-Armed BanditsAssessing parameter identifiability of a hemodynamics PDE model using spectral surrogates and dimension reduction
Computational inverse problems for biomedical simulators suffer from limited data and relatively high parameter dimensionality. This often requires sensitivity analysis, where parameters of the model are ranked based on …
Dimensionality ReductionExperimental DesignSensitivityProbabilistic Factorial Experimental Design for Combinatorial Interventions
A combinatorial intervention, consisting of multiple treatments applied to a single unit with potentially interactive effects, has substantial applications in fields such as biomedicine, engineering, and beyond. Given $p…
Experimental DesignExposing the Impact of GenAI for Cybercrime: An Investigation into the Dark Side
In recent years, the rapid advancement and democratization of generative AI models have sparked significant debate over safety, ethical risks, and dual-use concerns, particularly in the context of cybersecurity. While an…
Experimental DesignTime Series AnalysisCausal Inference for Experiments with Latent Outcomes: Key Results and Their Implications for Design and Analysis
How should researchers analyze randomized experiments in which the main outcome is measured in multiple ways but each measure contains some degree of error? We describe modeling approaches that enable researchers to iden…
Causal InferenceExperimental DesignregressionAdvancing the Scientific Method with Large Language Models: From Hypothesis to Discovery
With recent Nobel Prizes recognising AI contributions to science, Large Language Models (LLMs) are transforming scientific research by enhancing productivity and reshaping the scientific method. LLMs are now involved in …
Experimental DesignBehind the Noise: Conformal Quantile Regression Reveals Emergent Representations
Scientific imaging often involves long acquisition times to obtain high-quality data, especially when probing complex, heterogeneous systems. However, reducing acquisition time to increase throughput inevitably introduce…
DenoisingExperimental DesignImage Restorationquantile regression+1A suite of LMs comprehend puzzle statements as well as humans
Recent claims suggest that large language models (LMs) underperform humans in comprehending minimally complex English statements (Dentella et al., 2024). Here, we revisit those findings and argue that human performance w…
Experimental DesignConstrained Online Decision-Making: A Unified Framework
Contextual online decision-making problems with constraints appear in various real-world applications, such as personalized recommendation with resource limits and dynamic pricing with fairness constraints. In this paper…
Active LearningcounterfactualDecision MakingDensity Estimation+3Neurodivergent Influenceability as a Contingent Solution to the AI Alignment Problem
The AI alignment problem, which focusses on ensuring that artificial intelligence (AI), including AGI and ASI, systems act according to human values, presents profound challenges. With the progression from narrow AI to A…
Experimental DesignMathematical ProofsA CRISP approach to QSP: XAI enabling fit-for-purpose models
Quantitative Systems Pharmacology (QSP) promises to accelerate drug development, enable personalized medicine, and improve the predictability of clinical outcomes. Realizing this potential requires effectively managing t…
Experimental DesignDecoding Open-Ended Information Seeking Goals from Eye Movements in Reading
When reading, we often have specific information that interests us in a text. For example, you might be reading this paper because you are curious about LLMs for eye movements in reading, the experimental design, or perh…
Experimental Design