AIMC Topic: Quantum Theory

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Noncompact uniform universal approximation.

Neural networks : the official journal of the International Neural Network Society Feb 15, 2024
The universal approximation theorem is generalised to uniform convergence on the (noncompact) input space R. All continuous functions that vanish at infinity can be uniformly approximated by neural networks with one hidden layer, for all activation f...
Neural Networks, Computer Algorithms Quantum Theory
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From genome to clinic: The power of translational bioinformatics in improving human health.

Advances in protein chemistry and structural biology Feb 15, 2024
Translational bioinformatics (TBI) has transformed healthcare by providing personalized medicine and tailored treatment options by integrating genomic data and clinical information. In recent years, TBI has bridged the gap between genome and clinical...
Humans Artificial Intelligence Genomics Computational Biology Quantum Theory Computing Methodologies
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Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR.

Nature reviews. Drug discovery Dec 8, 2023
Quantitative structure-activity relationship (QSAR) modelling, an approach that was introduced 60 years ago, is widely used in computer-aided drug design. In recent years, progress in artificial intelligence techniques, such as deep learning, the rap...
Humans Artificial Intelligence Drug Design Drug Discovery Deep Learning Quantum Theory Quantitative Structure-Activity Relationship Computing Methodologies
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Quantum computing and machine learning for Arabic language sentiment classification in social media.

Scientific reports Oct 12, 2023
With the increasing amount of digital data generated by Arabic speakers, the need for effective and efficient document classification techniques is more important than ever. In recent years, both quantum computing and machine learning have shown grea...
Humans Machine Learning Language Social Media Quantum Theory Computing Methodologies Sentiment Analysis
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DASH: Dynamic Attention-Based Substructure Hierarchy for Partial Charge Assignment.

Journal of chemical information and modeling Sep 22, 2023
We present a robust and computationally efficient approach for assigning partial charges of atoms in molecules. The method is based on a hierarchical tree constructed from attention values extracted from a graph neural network (GNN), which was traine...
Neural Networks, Computer Quantum Theory
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Developing a User-Friendly Code for the Fast Estimation of Well-Behaved Real-Space Partial Charges.

Journal of chemical information and modeling Jun 20, 2023
The Quantum Theory of Atoms in Molecules (QTAIM) provides an intuitive, yet physically sound, strategy to determine the partial charges of any chemical system relying on the topology induced by the electron density ρ() . In a previous work [ , , 0141...
Machine Learning Software Quantum Theory
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Quantum computing for near-term applications in generative chemistry and drug discovery.

Drug discovery today Jun 16, 2023
In recent years, drug discovery and life sciences have been revolutionized with machine learning and artificial intelligence (AI) methods. Quantum computing is touted to be the next most significant leap in technology; one of the main early practical...
Artificial Intelligence Drug Discovery Quantum Theory Biological Science Disciplines Computing Methodologies
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Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry.

Journal of chemical information and modeling May 12, 2023
De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time- and resource-consuming, and it has a low probability of success. Recent advances in machine learni...
Humans Neural Networks, Computer Artificial Intelligence Pharmaceutical Preparations Quantum Theory Computing Methodologies
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An Efficient Approach to Large-Scale Ab Initio Conformational Energy Profiles of Small Molecules.

Molecules (Basel, Switzerland) Dec 5, 2022
Accurate conformational energetics of molecules are of great significance to understand maby chemical properties. They are also fundamental for high-quality parameterization of force fields. Traditionally, accurate conformational profiles are obtaine...
Neural Networks, Computer Quantum Theory Molecular Conformation Physical Phenomena
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DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials.

The journal of physical chemistry. A Dec 1, 2022
Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as de...
Machine Learning Quantum Theory Monte Carlo Method
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