Results 161 to 170 of about 1,378,752 (293)

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Level Number Sequences for Binary Trees [PDF]

Binary trees occur frequently in the ananlysis of computer algorithms and in such cases are usually only interested in the number of nodes at each level.
Wilson LB, Clowes JS, Mitrani I
core   +1 more source

The Enumeration of Left Ascending Binary Trees

, 2013
We will introduce and define a graph theory structure called left ascending binary trees. We count these trees by the number of vertices and the number of right children.
Scholten, Connor
core  

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

Fringe trees of Patricia tries and compressed binary search trees [PDF]

Most of the results in the paper for Patricia tries have earlier been proved by Jaspar Ischebeck. We study the distribution of fringe trees in Patricia tries and compressed binary search trees; both cases are random binary trees that have been ...
Janson, Svante
core  

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Tree-drawing test characteristics as potential predictors of adolescent depressive disorders. [PDF]

Ibrain
Lu Y, Chen X, Qiqige, Yi R, Bai J.
europepmc   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Observable Classification Patterns and Diagnostic Uncertainty in Parotid Ultrasound: A Multimethod Secondary Analysis. [PDF]

Diagnostics (Basel)
Pillong L, Walzer O, Peters M, Ohnesorg I, Palm J, Bozzato V, Garner M, Schick B, Bozzato A, Jäger T, Müller A, Pulham S, Voges M.   +12 more
europepmc   +1 more source

On Embedding Binary Trees into Hypercubes

, 1997
Hypercubes are known to be able to simulate other structures such as grids and binary trees. It has been shown that an arbitrary binary tree can be embedded into a hypercube with constant expansion and constant dilation.
Woei-kae Chen, Matthias F. M. Stallmann
core