A survey of Bayesian Network structure learning
Abstract Bayesian Networks (BNs) have become increasingly popular over the last few
decades as a tool for reasoning under uncertainty in fields as diverse as medicine, biology …
decades as a tool for reasoning under uncertainty in fields as diverse as medicine, biology …
Informed machine learning–a taxonomy and survey of integrating prior knowledge into learning systems
Despite its great success, machine learning can have its limits when dealing with insufficient
training data. A potential solution is the additional integration of prior knowledge into the …
training data. A potential solution is the additional integration of prior knowledge into the …
Machine learning assisted materials design and discovery for rechargeable batteries
Y Liu, B Guo, X Zou, Y Li, S Shi - Energy Storage Materials, 2020 - Elsevier
Abstract Machine learning plays an important role in accelerating the discovery and design
process for novel electrochemical energy storage materials. This review aims to provide the …
process for novel electrochemical energy storage materials. This review aims to provide the …
Machine‐Learning‐Assisted Nanozyme Design: Lessons from Materials and Engineered Enzymes
Nanozymes are nanomaterials that exhibit enzyme‐like biomimicry. In combination with
intrinsic characteristics of nanomaterials, nanozymes have broad applicability in materials …
intrinsic characteristics of nanomaterials, nanozymes have broad applicability in materials …
[HTML][HTML] Integrating machine learning with human knowledge
Machine learning has been heavily researched and widely used in many disciplines.
However, achieving high accuracy requires a large amount of data that is sometimes …
However, achieving high accuracy requires a large amount of data that is sometimes …
Evolution of safety and security risk assessment methodologies towards the use of bayesian networks in process industries
Process Industries handling, producing and storing bulk amount of hazardous materials are
a major source of concern in terms of both safety and security. Safety and security cannot be …
a major source of concern in terms of both safety and security. Safety and security cannot be …
High‐throughput experimentation and computational freeway lanes for accelerated battery electrolyte and interface development research
The timely arrival of novel materials plays a key role in bringing advances to society, as the
pace at which major technological breakthroughs take place is usually dictated by the …
pace at which major technological breakthroughs take place is usually dictated by the …
[HTML][HTML] Two optimal strategies for active learning of causal models from interventional data
From observational data alone, a causal DAG is only identifiable up to Markov equivalence.
Interventional data generally improves identifiability; however, the gain of an intervention …
Interventional data generally improves identifiability; however, the gain of an intervention …
Active learning: Problem settings and recent developments
H Hino - arxiv preprint arxiv:2012.04225, 2020 - arxiv.org
In supervised learning, acquiring labeled training data for a predictive model can be very
costly, but acquiring a large amount of unlabeled data is often quite easy. Active learning is …
costly, but acquiring a large amount of unlabeled data is often quite easy. Active learning is …
A survey of domain knowledge elicitation in applied machine learning
Eliciting knowledge from domain experts can play an important role throughout the machine
learning process, from correctly specifying the task to evaluating model results. However …
learning process, from correctly specifying the task to evaluating model results. However …