GitHub

MACHINE LEARNING FOR QUANTUM NOISE REDUCTION USING DENSITY MATRIX

Quantum computation has the potential for exponential speedup of classical systems in some applications, such as cryptography, simulation of molecular behavior, and optimization. Nevertheless, quantum ...
IEEE

Conv4Rec: A 1-by-1 Convolutional Autoencoder for User Profiling Through Joint Analysis of Implicit and Explicit Feedback

Abstract: We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility ...
IEEE

XChange: An Explainable Dynamic Convolutional Autoencoder for Unsupervised Change Detection

Abstract: Explainable artificial intelligence (XAI) approaches started to be studied in the last period to improve the interpretability of increasingly complex deep learning (DL) methods for remote ...
GitHub

A self-supervised clustering method combining adversarial autoencoders with cross-attention-based graph convolutional networks (GCN) for cell type identification in scRNA-seq ...

The code runs under Python 3.9.20 and Pytorch 2.3.1+cu121. Create a PyTorch environment and install required packages, such as "numpy", "pandas", "scikit-learn ...
C&EN

All That Glitters Is Not Gold: Importance of Rigorous Evaluation of Proteochemometric Models

Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States Department of Chemistry, Mellon College of Science, Carnegie ...