Results 11 to 20 of about 159,034 (226)
Interpretable machine learning [PDF]
Communications of the ACM, 2021 The emergence of machine learning as a society-changing technology in the past decade has triggered concerns about people's inability to understand the reasoning of increasingly complex models. The field of IML (interpretable machine learning) grew out of these concerns, with the goal of empowering various stakeholders to tackle use cases, such as ...
Chen, Valerie +4 more
openaire +2 more sources
Interpretable machine learning for genomics [PDF]
Human Genetics, 2021 AbstractHigh-throughput technologies such as next-generation sequencing allow biologists to observe cell function with unprecedented resolution, but the resulting datasets are too large and complicated for humans to understand without the aid of advanced statistical methods.
openaire +5 more sources
Techniques for interpretable machine learning [PDF]
Communications of the ACM, 2019 Uncovering the mysterious ways machine learning models make decisions.
Du, Mengnan, Liu, Ninghao, Hu, Xia
openaire +2 more sources
R.ROSETTA: an interpretable machine learning framework [PDF]
BMC Bioinformatics, 2019 AbstractMotivationFor machine learning to matter beyond intellectual curiosity, the models developed therefrom must be adopted within the greater scientific community. In this study, we developed an interpretable machine learning framework that allows identification of semantics from various datatypes.
Mateusz Garbulowski +8 more
openaire +7 more sources
Ultra-fast interpretable machine-learning potentials
npj Computational Materials, 2023 AbstractAll-atom dynamics simulations are an indispensable quantitative tool in physics, chemistry, and materials science, but large systems and long simulation times remain challenging due to the trade-off between computational efficiency and predictive accuracy. To address this challenge, we combine effective two- and three-body potentials in a cubic
Stephen R. Xie +2 more
openaire +4 more sources
Humanistic interpretation and machine learning [PDF]
Synthese, 2020 AbstractThis paper investigates how unsupervised machine learning methods might make hermeneutic interpretive text analysis more objective in the social sciences. Through a close examination of the uses of topic modeling—a popular unsupervised approach in the social sciences—it argues that the primary way in which unsupervised learning supports ...
Juho Pääkkönen, Petri Ylikoski
openaire +5 more sources
Machine learning interpretability meets TLS fingerprinting
Soft Computing, 2023 Protecting users' privacy over the Internet is of great importance; however, it becomes harder and harder to maintain due to the increasing complexity of network protocols and components. Therefore, investigating and understanding how data is leaked from the information transmission platforms and protocols can lead us to a more secure environment.
Mahdi Jafari Siavoshani +4 more
openaire +2 more sources
Interpretable machine learning for materials design
Journal of Materials Research, 2023 Fueled by the widespread adoption of Machine Learning (ML) and the high-throughput screening of materials, the data-centric approach to materials design has asserted itself as a robust and powerful tool for the in-silico prediction of materials properties.
James Dean +5 more
openaire +3 more sources
Interpretable machine learning for dementia: A systematic review
Alzheimer's & Dementia, 2023 AbstractIntroductionMachine learning research into automated dementia diagnosis is becoming increasingly popular but so far has had limited clinical impact. A key challenge is building robust and generalizable models that generate decisions that can be reliably explained.
Sophie A. Martin +3 more
openaire +4 more sources
Interpretable Machine Learning of Two‐Photon Absorption
Advanced Science, 2022 Abstract Molecules with strong two‐photon absorption (TPA) are important in many advanced applications such as upconverted laser and photodynamic therapy, but their design is hampered by the high cost of experimental screening and accurate quantum chemical (QC) calculations.
Yuming Su +9 more
openaire +3 more sources