Results 21 to 30 of about 14,567 (212)

Well-Founded Belief: An Introduction [PDF]

open access: yes, 2019
This is the Editor's Introduction to "Well-Founded Belief: New Essays on the Epistemic Basing Relation" (Routledge, 2020)
Bondy, Patrick, Carter, J. Adam
core  

Navigating Ternary Doping in Li‐ion Cathodes With Closed‐Loop Multi‐Objective Bayesian Optimization

open access: yesAdvanced Materials, EarlyView.
The search for advanced battery materials is pushing us into highly complex composition spaces. Here, a space with about 14 million unique combinations is efficiently explored using high‐throughput experimentation guided by Bayesian optimization with a deep kernel trained on both the Materials Project database and our data.
Nooshin Zeinali Galabi   +6 more
wiley   +1 more source

Standing in a Garden of Forking Paths [PDF]

open access: yes, 2018
According to the Path Principle, it is permissible to expand your set of beliefs iff (and because) the evidence you possess provides adequate support for such beliefs. If there is no path from here to there, you cannot add a belief to your belief set. If
A Brueckner   +34 more
core   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

open access: yesAdvanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Prime Time (for the Basing Relation) [PDF]

open access: yes, 2019
It is often assumed that believing that p for a normative reason consists in nothing more than (i) believing that p for a reason and (ii) that reason’s corresponding to a normative reason to believe that p, where (i) and (ii) are independent factors ...
Lord, Errol, Sylvan, Kurt
core   +1 more source

Shedding Light on Common Misinterpretations in Photocatalyst Characterization

open access: yesAdvanced Energy Materials, EarlyView.
For heterogeneous semiconductor‐based photocatalysts, Marschall et al. highlight common misconceptions in material synthesis, characterization, and performance evaluation, together with detailed explanations on how to avoid them. The guidelines thus presented can help to improve reporting of photocatalyst performance in environmental applications, such
Roland Marschall   +2 more
wiley   +1 more source

Defeaters and Disqualifiers [PDF]

open access: yes, 2019
Justification depends on context: even if E on its own justifies H, still it might fail to justify in the context of D. This sort of effect, epistemologists think, is due to defeaters, which undermine or rebut a would-be justifier.
Muñoz, Daniel
core  

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Knowledge Grounded on Pure Reasoning [PDF]

open access: yes, 2019
In this paper I deal with epistemological issues that stem from the hypothesis that reasoning is not only a means of transmitting knowledge from premise-beliefs to conclusion-beliefs, but also a primary source of knowledge in its own right.
Rosa, Luis
core   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park   +8 more
wiley   +1 more source

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