Results 141 to 150 of about 6,301,735 (343)

Representing biases for Inductive Logic Programming [PDF]

, 1994
Birgit Tausend
openalex   +1 more source

Engineering Relative Spatial Structure of Dual Atomic Sites with Asymmetric Coordination for High‐Performance Hydrogen Evolution Activity

Advanced Functional Materials, EarlyView.
Dual‐atom catalysts featuring varying spatial configurations of metal sites (Pt1Fe1 DACs) are employed to systematically investigate the influence of spatial arrangements on the electronic structure and catalytic activity of active sites. Notably, the 3D asymmetric Pt1Fe1‐TAC dimer, featuring strong interatomic interactions, demonstrates superior ...
Yi Guan, Xiaozhang Yao, Chuang Xue, Zhongxin Song, Xiangzhong Ren, Tsun‐Kong Sham, Li‐Min Liu, Lei Zhang, Xueliang Sun   +8 more
wiley   +1 more source

Meta-Interpretive LEarning with Reuse

Mathematics
Inductive Logic Programming (ILP) is a research field at the intersection between machine learning and logic programming, focusing on developing a formal framework for inductively learning relational descriptions in the form of logic programs from ...
Rong Wang, Jun Sun, Cong Tian, Zhenhua Duan   +3 more
doaj   +1 more source

Enhanced Nitric Oxide Electroreduction to Ammonia via Modulating Spin‐Polarization of Fe Single‐Atom Catalysts

Advanced Functional Materials, EarlyView.
A strategic spin‐polarization suppression in Fe single‐atom catalysts is proposed to enhance electrocatalytic reduction of NO to NH3. Employing a top‐down electrospinning strategy, self‐supported FeSAC with Fe‐N3S1 coordination structure and spin‐state transition is engineered from high‐spin to low‐spin.
Jialing Song, Ziqi Wei, Lupeng Han, Zhenlin Wang, Chenghao Fan, Donglin Han, Chunwei Dong, Haiyan Duan, Xiyang Wang, Sam Fong Yau Li, Eslam Hamed, Ming Xie, Emiliano Cortés, Dengsong Zhang   +13 more
wiley   +1 more source

Symbolic Imitation Learning: From Black-Box to Explainable Driving Policies

Applied Sciences
Current imitation learning approaches, predominantly based on deep neural networks (DNNs), offer efficient mechanisms for learning driving policies from real-world datasets.
Iman Sharifi, Mustafa Yildirim, Saber Fallah   +2 more
doaj   +1 more source

Drug design by machine learning: the use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase.

, 1992
Ross D. King, Stephen Muggleton, Richard A. Lewis, Michael J.E. Sternberg   +3 more
openalex   +2 more sources

Three-year evaluation of a program teaching social determinants of health in community-based medical education: a general inductive approach for qualitative data analysis [PDF]

, 2023
Sachiko Ozone, Junji Haruta, Ayumi Takayashiki, Takami Maeno, Tetsuhiro Maeno   +4 more
openalex   +1 more source

Cold Quad‐Modal Nanocomplex for Precise and Quantitative In Vivo Stem Cell Tracking

Advanced Functional Materials, EarlyView.
Multimodal albumin–bismuth sulfide–superparamagnetic iron oxide (ABS) nanocomplexes are developed for stem cell tracking across four different imaging modalities: MRI, MPI, MSOT, and CT. Combining its flexibility with high sensitivity, this quad‐modal imaging agent enables a robust quantification of ABS‐labeled stem cells in vivo.
Ali Shakeri‐Zadeh, Chao Wang, Shreyas Kuddannaya, Saleem Yousf, Jeff W. M. Bulte   +4 more
wiley   +1 more source

MP-HTHEDL: A Massively Parallel Hypothesis Evaluation Engine in Description Logic

IEEE Access
We present MP-HTHEDL, a massively parallel hypothesis evaluation engine for inductive learning in description logic (DL). MP-HTHEDL is an extension on our previous work HT-HEDL, which also targets improving hypothesis evaluation performance for inductive
Eyad Algahtani
doaj   +1 more source

Inductive Sequentialization of Asynchronous Programs (Evaluated Artifact)

, 2020
Bernhard Kragl, Constantin Enea, Thomas A. Henzinger, Süha Orhun Mutluergil, Shaz Qadeer   +4 more
openalex   +1 more source