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Probabilistic Logic Interpretation and Uncertainty Quantification of Neural Network Based Decision Making on Financial Time Series

https://doi.org/10.2139/ssrn.5280398
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Enhancing Time-Series Momentum Strategies Using Deep Neural Networks
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Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy
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Nonlinear Information Bottleneck
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Machine Learning in Resource-Scarce Embedded Systems, FPGAs, and End-Devices: A Survey
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An Overview of Machine Learning within Embedded and Mobile Devices–Optimizations and Applications
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Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
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Towards A Rigorous Science of Interpretable Machine Learning
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Making Logic Learnable With Neural Networks
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Bayesian Deep Learning and a Probabilistic Perspective of Generalization
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Financial Time Series Forecasting using CNN and Transformer
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A Model-Based Synthetic Stock Price Time Series Generation Framework
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The information bottleneck method
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Deep Differentiable Logic Gate Networks
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