26 papers · ranked by Valyu relevance
Anna Gorbunova, Anastasiia Kapuza, Ouhao Chen, Jamie Costley
This study examines how prior knowledge and pre-training relate to cognitive load during problem-solving. Grounded in cognitive load theory, it investigates whether pre-training facilitates learning by reducing cognitive load or imposes redundant information for learners with higher prior knowledge. In an experiment…
Caroline Bévalot, Florent Meyniel
The brain constantly uses prior knowledge of the statistics of its environment to shape perception. These statistics are often implicit (not directly observable) and gradually learned from observation; but they can also be explicitly communicated to the observer, especially in humans. In value-based decision-making…
Charles Findling, Felix Hubert, Luigi Acerbi, Brandon Benson + 52 more
The neural representations of prior information about the state of the world are poorly understood. To investigate this issue, we examined brain-wide Neuropixels recordings and widefield calcium imaging collected by the International Brain Laboratory. Mice were trained to indicate the location of a visual grating…
Cécile Gal, Ioana Țincaș, Vasile V. Moca, Andrei Ciuparu + 4 more
Recognising objects is a vital skill on which humans heavily rely to respond quickly and adaptively to their environment. Yet, we lack understanding on the role visual information sampling plays in this process, and its relation to the individual’s priors. To bridge this gap, the eye-movements of 18 adult participants…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…
Jacques Balayla
We define the information threshold as the point of maximum curvature in the prior vs. posterior Bayesian curve, both of which are described as a function of the true positive and negative rates of the classification system in question. The nature of the threshold is such that for sufficiently adequate binary…
Wen Wen, Yichen Wu, Robert M.G. Reinhart, Sheng Li
The brain processes vast information every second, much of which is irrelevant. Given the massive distracting information in which a target is embedded, the ability to manage distractions becomes the determinant of efficient information processing. Fortunately, the visual world is not entirely random; prior knowledge…
Ryan Martin
Between Bayesian and frequentist inference, it's commonly believed that the former is for cases where one has a prior and the latter is for cases where one has no prior. But the prior/no-prior classification isn't exhaustive, and most real-world applications fit somewhere in between these two extremes. That neither of…
Hanti Lin
The problem of the priors is well known: it concerns the challenge of identifying norms that govern one's prior credences. I argue that a key to addressing this problem lies in considering what I call the problem of the posteriors—the challenge of identifying norms that directly govern one's posterior credences, which…
Reid Dale
This paper is concerned with the epistemic question of confirming a hypothesis—the guilt of a defendant—by way of testimony heard by a juror over the course of an American-style criminal trial. In it, I attempt to settle a dispute between two strands of the legal community over the issue of whether the methods of…
Authors not listed
Surfactants are widely used for industrial applications, yet more environmentally-friendly surfactants with enhanced properties are demanded. A key thermodynamic property governing the behavior of a surfactant in an aqueous solution is its critical micelle concentration (CMC). Below the CMC, increasing the surfactant…
Cailleteau Thomas
In this second article, we show a simple use of the Ignorance as defined in a previous article Jaynes & Shannon's Constrained Ignorance and Surprise. By giving an example about the journey of a person, we believe to show some simple, obvious but mathematically encoded philosophical implications about how we could…
Claire Field
In this paper, I discuss Whiting’s ([19]) account of rational belief and discuss some unresolved issues arising from its reliance on epistemic possibility and, by extension, perspective-relative aprioricity.
Jonas M. Mikhaeil, Donald P. Green
How much does a research study contribute to a scientific literature? We propose a learning metric to quantify how much a research community learns from a given study. To do so, we adopt a Bayesian perspective and assess changes in the community's beliefs once updated with a new study's evidence. We recommend the…
Chin-Hsuan Sophie Lin, Trang Thuy Do, Lee Unsworth, Marta I. Garrido
Numerous studies have found that the Bayesian framework, which formulates the optimal integration of the knowledge of the world (i.e. prior) and current sensory evidence (i.e. likelihood), captures human behaviours sufficiently well. However, there are debates regarding whether humans use precise but cognitively…
Kan Hatakeyama-Sato, Seigo Watanabe, Naoki Yamane, Yasuhiko Igarashi + 1 more
Materials informatics and cheminformatics struggle with data scarcity, hindering the extraction of significant relationships between structures and properties. The "Ugly Duckling" theorem, suggesting the difficulty of data processing without assumptions or prior knowledge, exacerbates this problem. Current…
Timothy Kearl
Two traditions in action theory offer different accounts of what distinguishes intentional action from mere behavior. According to the causalist tradition, intentional action has certain distinguished causal antecedents, and according to the Anscombian tradition, intentional action has certain distinguished…
Ola Hössjer, Daniel Andrés Díaz-Pachón, J. Sunil Rao, Deniz Gençağa
Philosophers frequently define knowledge as justified, true belief. We built a mathematical framework that makes it possible to define learning (increasing number of true beliefs) and knowledge of an agent in precise ways, by phrasing belief in terms of epistemic probabilities, defined from Bayes’ rule. The degree of…
Meshandren Naidoo
Information, as the most elusive subject, is central to all forms of thought, governance, economic structure, science, and society. Regulation of information, especially within the healthcare field, is proving to be a difficult task globally, given the lack of a qualitative framework and understanding of the concept…
Daniel Andrés Díaz–Pachón, H. Renata Gallegos, Ola Hössjer, J. Sunil Rao
'J. Sunil Rao'] In this paper, we study learning and knowledge acquisition (LKA) of an agent about a proposition that is either true or false. We use a Bayesian approach, where the agent receives data to update his beliefs about the proposition according to a posterior distribution. The LKA is formulated in terms of…
Authors not listed
Identifying synthesis routes from knowledge graphs poses challenges beyond retrosynthesis, including path–finding artifacts and data issues. We introduce “SynGPS”, a novel algorithm that overcomes these limitations by identifying viable routes even with common artifacts. SynGPS can resolve nonsensical cycles…
Constanza Fierro, Ruchira Dhar, Filippos Stamatiou, Nicolas Garneau + 1 more
'Anders Søgaard'] Knowledge claims are abundant in the literature on large language models (LLMs); but can we say that GPT-4 truly "knows" the Earth is round? To address this question, we review standard definitions of knowledge in epistemology and we formalize interpretations applicable to LLMs. In doing so, we…
Michael Moret, Francesca Grisoni, Paul Katzberger, Gisbert Schneider
Chemical language models (CLMs) can be employed to design molecules with desired properties. CLMs generate new chemical structures in the form of textual representations, such as the simplified molecular input line entry systems (SMILES) strings, in a rule-free manner. However, the quality of these de novo generated…
Authors not listed
Kinetic modeling is essential for predicting changes in food quality during processing and storage. This study evaluates the application of physics-informed neural networks (PINN) for food kinetic modeling, integrating kinetic insights into neural network frameworks. Based on three case studies, namely seed drying…
Authors not listed
In philosophy and science, a first principle is a basic proposition or assumption that cannot be deduced from any other proposition or assumption. Ancient Greek philosophy Aristotle defined the first principle as “the first basis from which a thing is known.” First principles thinking (or reasoning from first…