Results 91 to 100 of about 9,420,561 (398)

The Definitions of Interpretability and Learning of Interpretable Models [PDF]

open access: yesarXiv, 2021
As machine learning algorithms getting adopted in an ever-increasing number of applications, interpretation has emerged as a crucial desideratum. In this paper, we propose a mathematical definition for the human-interpretable model. In particular, we define interpretability between two information process systems. If a prediction model is interpretable
arxiv  

Re-interpreting interpreting

open access: yesTranslation Studies, 2023
The abstract is available here: https://uscholar.univie.ac.at/o ...
openaire   +1 more source

Designing as Interpretation [PDF]

open access: yes, 2009
The paper suggests an interpretative approach to the empirical study of design processes. Design processes are conceived as social processes of interpretation and construction of meaning, and potentially of context generation. In contrast to models which
Glock, Friedrich
core  

Brucella NyxA and NyxB dimerization enhances effector function during infection

open access: yesFEBS Letters, EarlyView.
Brucella abortus thrives inside cells thanks to the translocation of effector proteins that fine‐tune cellular functions. NyxA and NyxB are two effectors that destabilize the nucleolar localization of their host target, SENP3. We show that the Nyx proteins directly interact with each other and that their dimerization is essential for their function ...
Lison Cancade‐Veyre   +4 more
wiley   +1 more source

There is no first quantization - except in the de Broglie-Bohm interpretation [PDF]

open access: yesarXiv, 2003
The relativistic effects of the integer-spin quantum field theory imply that the wave functions describing a fixed number of particles do not admit the usual probabilistic interpretation. Among several most popular interpretations of quantum mechanics applied to first quantization, the only interpretation for which this fact does not lead to a serious ...
arxiv  

Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability [PDF]

open access: yesarXiv, 2020
Recent years have witnessed an increasing number of interpretation methods being developed for improving transparency of NLP models. Meanwhile, researchers also try to answer the question that whether the obtained interpretation is faithful in explaining mechanisms behind model prediction? Specifically, (Jain and Wallace, 2019) proposes that "attention
arxiv  

On the Effectiveness of Interpretable Feedforward Neural Network [PDF]

open access: yesarXiv, 2021
Deep learning models have achieved state-of-the-art performance in many classification tasks. However, most of them cannot provide an interpretation for their classification results. Machine learning models that are interpretable are usually linear or piecewise linear and yield inferior performance.
arxiv  

B cell mechanobiology in health and disease: emerging techniques and insights into therapeutic responses

open access: yesFEBS Letters, EarlyView.
B cells sense external mechanical forces and convert them into biochemical signals through mechanotransduction. Understanding how malignant B cells respond to physical stimuli represents a groundbreaking area of research. This review examines the key mechano‐related molecules and pathways in B lymphocytes, highlights the most relevant techniques to ...
Marta Sampietro   +2 more
wiley   +1 more source

Interpretations of Linear Orderings in Presburger Arithmetic [PDF]

open access: yesarXiv, 2019
Presburger Arithmetic $\mathop{\mathbf{PrA}}\nolimits$ is the true theory of natural numbers with addition. We consider linear orderings interpretable in Presburger Arithmetic and establish various necessary and sufficient conditions for interpretability depending on dimension $n$ of interpretation.
arxiv  

Implicit Mixture of Interpretable Experts for Global and Local Interpretability [PDF]

open access: yesarXiv, 2022
We investigate the feasibility of using mixtures of interpretable experts (MoIE) to build interpretable image classifiers on MNIST10. MoIE uses a black-box router to assign each input to one of many inherently interpretable experts, thereby providing insight into why a particular classification decision was made.
arxiv  

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