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Found 4 papers, 0 papers with code
Improving CNN-base Stock Trading By Considering Data Heterogeneity and Burst
In recent years, there have been quite a few attempts to apply intelligent techniques to financial trading, i. e., constructing automatic and intelligent trading framework based on historical stock price.
Making Invisible Visible: Data-Driven Seismic Inversion with Spatio-temporally Constrained Data Augmentation
To validate the effectiveness of our data augmentation techniques, we apply them to solve a subsurface seismic full-waveform inversion using simulated CO$_2$ leakage data.
GenQu: A Hybrid Framework for Learning Classical Data in Quantum States
In this paper, we propose GenQu, a hybrid and general-purpose quantum framework for learning classical data through quantum states.
In situ TensorView: In situ Visualization of Convolutional Neural Networks
We present in situ TensorView to visualize the training and functioning of CNNs as if they are systems of scientific simulations.
