Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
[HTML][HTML] Applications of machine learning in antibody discovery, process development, manufacturing and formulation: current trends, challenges, and opportunities
While machine learning (ML) has made significant contributions to the biopharmaceutical
field, its applications are still in the early stages in terms of providing direct support for quality …
field, its applications are still in the early stages in terms of providing direct support for quality …
Learning under concept drift for regression—a systematic literature review
Context: The amount and diversity of data have increased drastically in recent years.
However, in certain situations, the data to which a trained Machine Learning model is …
However, in certain situations, the data to which a trained Machine Learning model is …
Learning data streams with changing distributions and temporal dependency
In a data stream, concept drift refers to unpredictable distribution changes over time, which
violates the identical-distribution assumption required by conventional machine learning …
violates the identical-distribution assumption required by conventional machine learning …
The technological emergence of automl: A survey of performant software and applications in the context of industry
With most technical fields, there exists a delay between fundamental academic research and
practical industrial uptake. Whilst some sciences have robust and well-established …
practical industrial uptake. Whilst some sciences have robust and well-established …
Autonoml: Towards an integrated framework for autonomous machine learning
Over the last decade, the long-running endeavour to automate high-level processes in
machine learning (ML) has risen to mainstream prominence, stimulated by advances in …
machine learning (ML) has risen to mainstream prominence, stimulated by advances in …
Multiple adaptive mechanisms for data-driven soft sensors
Recent data-driven soft sensors often use multiple adaptive mechanisms to cope with non-
stationary environments. These mechanisms are usually deployed in a prescribed order …
stationary environments. These mechanisms are usually deployed in a prescribed order …
Automatic composition and optimization of multicomponent predictive systems with an extended auto-WEKA
Composition and parameterization of multicomponent predictive systems (MCPSs)
consisting of chains of data transformation steps are a challenging task. Auto-WEKA is a tool …
consisting of chains of data transformation steps are a challenging task. Auto-WEKA is a tool …
Applications of machine learning in biopharmaceutical process development and manufacturing: Current trends, challenges, and opportunities
While machine learning (ML) has made significant contributions to the biopharmaceutical
field, its applications are still in the early stages in terms of providing direct support for quality …
field, its applications are still in the early stages in terms of providing direct support for quality …
Adapting multicomponent predictive systems using hybrid adaptation strategies with auto-weka in process industry
Automation of composition and optimisation of multicomponent predictive systems (MCPSs)
made of a number of preprocessing steps and predictive models is a challenging problem …
made of a number of preprocessing steps and predictive models is a challenging problem …
Automated adaptation strategies for stream learning
Automation of machine learning model development is increasingly becoming an
established research area. While automated model selection and automated data pre …
established research area. While automated model selection and automated data pre …