The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stoc...
However, accurate multivariate financial time series forecasting remains a challenge due to its complex nonlinear pattern. Aiming to fill the gap in the field, a novel forecasting framework, based on a two-stage feature selection model, deep learning model, and error correction model, is presented...
A deep reinforcement learning framework and its implementation for UAV-aided covert communication S. FU, Y. SU, Z. ZHANG and L. YIN Star point positioning for large dynamic star sensors in near space based on capsule network Z. LIAO, H. WANG, X. ZHENG, Y. ZANG, Y. LU and S. YAO ...
Deep learning based framework for segmentation and analysis of WSI images. Drawn using draw.io (draw.io). Full size image Materials and methods This section goes into the details of the proposed framework. Firstly, the ensemble and the network architectures are detailed. Secondly, the strategies ...
4、deep learning models [8, 45, 52] have shown muchsuperior performance than previous three categories of models dueto its capability of modeling complex user-item relationship 2.2 Reinforcement learning inrecommendation 2.2.1 Contextual Multi-Armed Bandit models ...
Abstract We present fVDB, a novel GPU-optimized framework for deep learning on large-scale 3D data. fVDB provides a complete set of differentiable primitives to build deep learning architectures for common tasks in 3D learning such as convolution, pooling, attention, ray-tracing, meshing, etc. ...
K. (2023). Forecasting stock market prices using machine learning and deep learning models: A systematic review, performance analysis and discussion of implications. International Journal of Financial Studies, 11(3), 94. Article Google Scholar Spence, C. (2021). Explaining seasonal patterns of ...
A framework for high-performance medical image processing, neural network inference and visualization fast.eriksmistad.no Topics visualization python streaming deep-learning opencl parallel-computing image-processing medical-imaging gpu-computing ultrasound digital-pathology Resources Readme License BSD-2...
Systems neuroscience seeks explanations for how the brain implements a wide variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to design computational systems based on the tasks they will have to solve. In arti
In this letter, a new deep learning framework for spectral–spatial classification of hyperspectral images is presented. The proposed framework serves as an engine for merging the spatial and spectral features via suitable deep learning architecture: stacked autoencoders (SAEs) and deep convolutional ne...