Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
In feed-forward neural networks, dataset-free weight-initialization methods such as LeCun, Xavier (or Glorot), and He initializations have been developed. These methods randomly determine the initial values of weight parameters based on specific dist...
International journal of neural systems
Jun 1, 2025
Deep neural networks struggle with incremental updates due to catastrophic forgetting, where newly acquired knowledge interferes with the learned previously. Continual learning (CL) methods aim to overcome this limitation by effectively updating the ...
Journal of chemical information and modeling
May 26, 2025
Coumarin derivatives have been widely developed and utilized as chromophores and fluorophores in various research fields. In this study, we constructed an experimental database of the optical properties─specifically, absorption and emission wavelengt...
Communications biology
May 25, 2025
Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when ...
Military medicine
Aug 19, 2024
INTRODUCTION: Computational head injury models are promising tools for understanding and predicting traumatic brain injuries. However, most available head injury models are "average" models that employ a single set of head geometry (e.g., 50th-percen...
Bioinformatics (Oxford, England)
Sep 2, 2023
MOTIVATION: Learning low-dimensional representations of single-cell transcriptomics has become instrumental to its downstream analysis. The state of the art is currently represented by neural network models, such as variational autoencoders, which us...
The Journal of chemical physics
Sep 14, 2022
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree-Fock computations. A MOB pairwise decomposition ...
Mathematical biosciences and engineering : MBE
Jul 27, 2022
With the unprecedented development of big data, it is becoming hard to get the valuable information hence, the recommendation system is becoming more and more popular. When the limited Boltzmann machine is used for collaborative filtering, only the s...
Neural computation
May 19, 2022
We develop a general framework for statistical inference with the 1-Wasserstein distance. Recently, the Wasserstein distance has attracted considerable attention and has been widely applied to various machine learning tasks because of its excellent p...
Physical review letters
Apr 22, 2022
Criticality is deeply related to optimal computational capacity. The lack of a renormalized theory of critical brain dynamics, however, so far limits insights into this form of biological information processing to mean-field results. These methods ne...