Spin-Symmetry-Enforced Solution of the Many-Body Schrödinger Equation with a Deep Neural Network

Physics, Quantum Physics, Chemistry, Computational Chemistry, Information Science, Artificial Intelligence,
deep neural networks   Schrödinger equation   spin symmetry   quantum states   photochemistry   multi-reference systems   electron correlation  

Research on Deep Learning Framework for Spin-Symmetry-Enforced Solutions to the Many-Body Schrödinger Equation: A Groundbreaking Achievement In the fields of quantum physics and quantum chemistry, the description of many-body electron systems has always been an important yet highly challenging topic. Accurately characterizing strong electron-electr...

Knowledge Probabilization in Ensemble Distillation: Improving Accuracy and Uncertainty Quantification for Object Detectors

Information Science, Computer Science, Artificial Intelligence,
knowledge probabilization   ensemble distillation   object detection   uncertainty quantification   deep neural networks   accuracy improvement   feature knowledge  

Research on the Application of Knowledge Probabilization in Ensemble Distillation Academic Background: Significance of the Research and Problem Statement In recent years, deep neural networks (DNNs) have found broad applications in safety-critical fields such as autonomous driving, medical diagnosis, and climate prediction due to their outstanding ...

An Invisible, Robust Protection Method for DNN-Generated Content

Information Science, Artificial Intelligence,
deep neural networks   invisible perturbation   protection technique   robustness   generated content   image encoding   social media  

Invisible and Robust Protection Method for Content Generated by Deep Neural Networks Academic Background In recent years, with the revolutionary development and widespread application of deep learning models in engineering applications, phenomenon-level applications such as ChatGPT and DALL⋅E 2 have emerged, profoundly impacting people’s daily live...

Using Deep Neural Networks to Disentangle Visual and Semantic Information in Human Perception and Memory

Information Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Biophysics,
deep neural networks   visual information   semantic information   human perception   memory   visual-semantic representation   mental representation  

Differentiating Visual and Semantic Information in Human Perception and Memory Using Deep Neural Networks Introduction In cognitive science, the study of how humans recognize individuals and objects during perception and memory processes has long been of interest. Successful recognition of people and objects relies on matching representations gener...