Machine learning for condensed matter physics

E Bedolla, LC Padierna… - Journal of Physics …, 2020 - iopscience.iop.org
Condensed matter physics (CMP) seeks to understand the microscopic interactions of matter
at the quantum and atomistic levels, and describes how these interactions result in both …

Deep learning for volatility forecasting in asset management

A Petrozziello, L Troiano, A Serra, I Jordanov, G Storti… - Soft Computing, 2022 - Springer
Predicting volatility is a critical activity for taking risk-adjusted decisions in asset trading and
allocation. In order to provide effective decision-making support, in this paper we investigate …

Km4: Visual reasoning via knowledge embedding memory model with mutual modulation

W Zheng, L Yan, C Gou, FY Wang - Information Fusion, 2021 - Elsevier
Visual reasoning is a special kind of visual question answering, which is essentially multi-
step and compositional, and also requires intensive text-visual interaction. The most …

A multi-memory-augmented network with a curvy metric method for video anomaly detection

H Li, Y Wang, Y Wang, J Chen - Neural Networks, 2025 - Elsevier
Anomaly detection task in video mainly refers to identifying anomalous events that do not
conform to the learned normal patterns in the inferring phase. However, the Euclidean metric …

BERT gated multi-window attention network for relation extraction

S Xu, S Sun, Z Zhang, F Xu, J Liu - Neurocomputing, 2022 - Elsevier
Entity relation extraction aims to identify the semantic relation between entity pairs in a
sentence and is an important technical support for downstream tasks such as question …

Research into ship trajectory prediction based on an improved LSTM network

J Zhang, H Wang, F Cui, Y Liu, Z Liu… - Journal of Marine Science …, 2023 - mdpi.com
The establishment of ship trajectory prediction is critical in analyzing trajectory data. It serves
as a critical reference point for identifying abnormal behavior and potential collision risks for …

DCT based multi-head attention-BiGRU model for EEG source location

B Zhang, D Li, D Wang - Biomedical Signal Processing and Control, 2024 - Elsevier
Electroencephalogram source imaging (ESI) pertains to localize brain sources. Due to the
one-to-many relationship between electroencephalogram (EEG) signals and brain sources …

Precision enhancement by compensation of hemispherical resonator gyroscope dynamic output errors

YX Li, BQ Xi, SQ Ren, CH Wang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In order to compensate for the hemispherical resonator gyroscope (HRG) dynamic output
drift errors, a novel compensation method is presented. Through deriving the resonator …

Diagnosis of unbalance in lightweight rotating machines using a recurrent neural network suitable for an edge-computing framework

LY Imamura, SL Avila, FS Pacheco, MBC Salles… - Journal of Control …, 2022 - Springer
Fault diagnostics is essential for improving the reliability of electrical machines applied in
smart manufacturing. For many industrial applications, AI-based solutions become viable …

Data-driven intelligent warning method for membrane fouling

X Wu, H Han, J Qiao - IEEE Transactions on Neural Networks …, 2021 - ieeexplore.ieee.org
Membrane fouling has become a serious issue in membrane bioreactor (MBR) and may
destroy the operation of the wastewater treatment process (WWTP). The goal of this article is …