Results 51 to 60 of about 14,505 (295)

Epistemic Wrapping for Uncertainty Quantification

CoRR
Uncertainty estimation is pivotal in machine learning, especially for classification tasks, as it improves the robustness and reliability of models. We introduce a novel `Epistemic Wrapping' methodology aimed at improving uncertainty estimation in classification.
Maryam Sultana, Neil Yorke-Smith, Kaizheng Wang, Shireen Kudukkil Manchingal, Muhammad Mubashar, Fabio Cuzzolin   +5 more
openaire   +2 more sources

Representation of analysis results involving aleatory and epistemic uncertainty. [PDF]

, 2008
Procedures are described for the representation of results in analyses that involve both aleatory uncertainty and epistemic uncertainty, with aleatory uncertainty deriving from an inherent randomness in the behavior of the system under study and ...
Helton, Jon Craig (Arizona State University, Tempe, AZ), Oberkampf, William Louis, Sallaberry, Cedric J., Johnson, Jay Dean (ProStat, Mesa, AZ)   +3 more
core   +1 more source

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

Advanced 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

Epistemic uncertainties and natural hazard risk assessment – Part 1: A review of different natural hazard areas [PDF]

Natural Hazards and Earth System Sciences, 2018
This paper discusses how epistemic uncertainties are currently considered in the most widely occurring natural hazard areas, including floods, landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and ...
K. J. Beven, K. J. Beven, S. Almeida, W. P. Aspinall, P. D. Bates, S. Blazkova, E. Borgomeo, J. Freer, K. Goda, J. W. Hall, J. C. Phillips, M. Simpson, P. J. Smith, P. J. Smith, D. B. Stephenson, T. Wagener, T. Wagener, M. Watson, K. L. Wilkins   +18 more
doaj   +1 more source

Fast performance uncertainty estimation via pushover and approximate IDA

, 2009
Approximate methods based on the static pushover are introduced to estimate the seismic performance uncertainty of structures having non-deterministic modeling parameters. At their basis lies the use of static pushover analysis to approximate Incremental
Vamvatsikos, D., Fragiadakis, M., Vamvatsikos, D, Fragiadakis, M   +3 more
core   +1 more source

Admissibility and event-rationality [PDF]

, 2013
We develop an approach to providing epistemic conditions for admissible behavior in games. Instead of using lexicographic beliefs to capture infinitely less likely conjectures, we postulate that players use tie-breaking sets to help decide among ...
Galanis, Spyros, Galanis, S., Barelli, Paulo, Barelli, M.   +3 more
core   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

CAPO: Causal-Adaptive Preference Optimization for Diffusion Models via Causal Inference Uncertainty

IEEE Access
Post-training alignment of diffusion models based on human feedback uniformly applies equal weights to all preference pairs, ignoring the inherent aleatoric and epistemic uncertainty in feedback, leading to overfitting on noisy signals and insufficient ...
Sihan Hu
doaj   +1 more source

Practice-dependence and epistemic uncertainty

, 2017
A shared presumption among practice-dependent theorists is that a principle of justice is dependent on the function or aim of the practice to which it is supposed to be applied.
Niklas Möller, Möller, Niklas, Eva Erman, Erman, Eva,, Möller, Niklas,, Erman, E.   +5 more
core   +1 more source

Prior Expectations Bias Confidence Judgments Through Parietal Alpha‐Band Modulation

Advanced Science, EarlyView.
ABSTRACT Humans possess the metacognitive ability to estimate the likely accuracy of their own decisions through confidence judgments. Yet, whether prior information shapes confidence and the neural mechanisms mediating such influence, remain to be determined.
Luca Tarasi, Anna Pasini, Domenico Romanazzi, Margherita Covelli, Vincenzo Romei   +4 more
wiley   +1 more source