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Discovering causal relations and equations from data
Physics is a field of science that has traditionally used the scientific method to answer
questions about why natural phenomena occur and to make testable models that explain the …
questions about why natural phenomena occur and to make testable models that explain the …
Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …
traditional research paradigms in the era of artificial intelligence and automation. An …
Automated discovery of fundamental variables hidden in experimental data
All physical laws are described as mathematical relationships between state variables.
These variables give a complete and non-redundant description of the relevant system …
These variables give a complete and non-redundant description of the relevant system …
Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics
The use of statistical/machine learning (ML) approaches to materials science is
experiencing explosive growth. Here, we review recent work focusing on the generation and …
experiencing explosive growth. Here, we review recent work focusing on the generation and …
[ספר][B] Data-driven fluid mechanics: combining first principles and machine learning
MA Mendez, A Ianiro, BR Noack, SL Brunton - 2023 - books.google.com
Data-driven methods have become an essential part of the methodological portfolio of fluid
dynamicists, motivating students and practitioners to gather practical knowledge from a …
dynamicists, motivating students and practitioners to gather practical knowledge from a …
Physical laboratory automation in synthetic biology
Synthetic Biology has overcome many of the early challenges facing the field and is entering
a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches …
a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches …
Autonomous molecular design: then and now
The success of deep machine learning in processing of large amounts of data, for example,
in image or voice recognition and generation, raises the possibilities that these tools can …
in image or voice recognition and generation, raises the possibilities that these tools can …
Integrating autonomy into automated research platforms
Integrating automation and autonomy into self-driving laboratories promises more efficient
and reproducible experimentation while freeing scientists to focus on intellectual challenges …
and reproducible experimentation while freeing scientists to focus on intellectual challenges …
Role of robotic process automation in pharmaceutical industries
N Bhatnagar - The International Conference on Advanced Machine …, 2020 - Springer
Abstract Robotic Process Automation (RPA) is a technological revolution in the offing and is
aimed at taking up the mundane and repetitive tasks from people's daily workload. It throws …
aimed at taking up the mundane and repetitive tasks from people's daily workload. It throws …
[HTML][HTML] How technoscientific knowledge advances: A Bell-Labs-inspired architecture
Understanding how science and technology advance has long been of interest to diverse
scholarly communities. Thus far, however, such understanding has not been easy to map to …
scholarly communities. Thus far, however, such understanding has not been easy to map to …