Zobrazeno 1 - 10
of 52 259
pro vyhledávání: '"Samuel, J."'
Autor:
Bell, Samuel J., Meglioli, Mariano Coria, Richards, Megan, Sánchez, Eduardo, Ropers, Christophe, Wang, Skyler, Williams, Adina, Sagun, Levent, Costa-jussà, Marta R.
Text toxicity detection systems exhibit significant biases, producing disproportionate rates of false positives on samples mentioning demographic groups. But what about toxicity detection in speech? To investigate the extent to which text-based biase
Externí odkaz:
http://arxiv.org/abs/2411.08135
Autor:
Bell, Samuel J., Wang, Skyler
Learning correlations from data forms the foundation of today's machine learning (ML) and artificial intelligence (AI) research. While such an approach enables the automatic discovery of patterned relationships within big data corpora, it is suscepti
Externí odkaz:
http://arxiv.org/abs/2411.04696
Does learning of task-relevant representations stop when behavior stops changing? Motivated by recent theoretical advances in machine learning and the intuitive observation that human experts continue to learn from practice even after mastery, we hyp
Externí odkaz:
http://arxiv.org/abs/2411.03541
Neural optical flow (NOF) offers improved accuracy and robustness over existing OF methods for particle image velocimetry (PIV). Unlike other OF techniques, which rely on discrete displacement fields, NOF parameterizes the physical velocity field usi
Externí odkaz:
http://arxiv.org/abs/2411.02373
Relationships between plants and insects vitally underpin the health of global ecosystems and food production. Through co-evolution, insects have acquired a variety of senses in response to the emergence of floral cues such as scent, colour and shape
Externí odkaz:
http://arxiv.org/abs/2411.02195
This paper introduces SpineFM, a novel pipeline that achieves state-of-the-art performance in the automatic segmentation and identification of vertebral bodies in cervical and lumbar spine radiographs. SpineFM leverages the regular geometry of the sp
Externí odkaz:
http://arxiv.org/abs/2411.00326
Many promising explosion models for the elusive origin of Type Ia supernovae (SNe Ia) ultimately fail to completely reproduce a number of observed properties of these events. One limiting factor for many of these models is the use of the local thermo
Externí odkaz:
http://arxiv.org/abs/2410.22276
In this study, we present a method for predicting the representativity of the phase fraction observed in a single image (2D or 3D) of a material. Traditional approaches often require large datasets and extensive statistical analysis to estimate the I
Externí odkaz:
http://arxiv.org/abs/2410.19568
The features of self-supervised vision transformers (ViTs) contain strong semantic and positional information relevant to downstream tasks like object localization and segmentation. Recent works combine these features with traditional methods like cl
Externí odkaz:
http://arxiv.org/abs/2410.19836
We show how the effects of large numbers of measurements on many-body quantum ground and thermal states can be studied using Quantum Monte Carlo (QMC). Density matrices generated by measurement in this setting feature products of many local nonunitar
Externí odkaz:
http://arxiv.org/abs/2410.13844