129 results on '"Xiong, YiHui"'
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2. Effects of Fluid Pressure Development on Hydrothermal Mineralization via Cellular Automaton Simulation
3. Dual-Branch Convolutional Neural Network and Its Post Hoc Interpretability for Mapping Mineral Prospectivity
4. ArcMPM: An ArcEngine-Based Software for Mineral Prospectivity Mapping via Artificial Intelligence Algorithms
5. A New Generation of Artificial Intelligence Algorithms for Mineral Prospectivity Mapping
6. Metallogenic-Factor Variational Autoencoder for Geochemical Anomaly Detection by Ad-Hoc and Post-Hoc Interpretability Algorithms
7. Revealing Geochemical Patterns Associated with Mineralization Using t-Distributed Stochastic Neighbor Embedding and Random Forest
8. An interpretable attention branch convolutional neural network for identifying geochemical anomalies related to mineralization
9. Visual Interpretable Deep Learning Algorithm for Geochemical Anomaly Recognition
10. Modeling singular mineralization processes due to fluid pressure fluctuations
11. Mineral Prospectivity Mapping via Gated Recurrent Unit Model
12. A Geologically Constrained Variational Autoencoder for Mineral Prospectivity Mapping
13. A Physically Constrained Variational Autoencoder for Geochemical Pattern Recognition
14. Robust Feature Extraction for Geochemical Anomaly Recognition Using a Stacked Convolutional Denoising Autoencoder
15. A fractal model of granitic intrusion and variability based on cellular automata
16. A geologically-constrained deep learning algorithm for recognizing geochemical anomalies
17. GIS, Geostatistics, and Machine Learning in Medical Geology
18. Uncertainties in GIS-Based Mineral Prospectivity Mapping: Key Types, Potential Impacts and Possible Solutions
19. Knowledge discovery of geochemical patterns from a data-driven perspective
20. Distinguishing IOCG and IOA deposits via random forest algorithm based on magnetite composition
21. A positive and unlabeled learning algorithm for mineral prospectivity mapping
22. Random-Drop Data Augmentation of Deep Convolutional Neural Network for Mineral Prospectivity Mapping
23. Geodata science and geochemical mapping
24. Mapping Mineral Prospectivity via Semi-supervised Random Forest
25. Deep learning and its application in geochemical mapping
26. A Spatially Constrained Multi-Autoencoder approach for multivariate geochemical anomaly recognition
27. Mapping mineral prospectivity through big data analytics and a deep learning algorithm
28. Identification of geochemical anomalies via local RX anomaly detector
29. Recognizing geochemical patterns related to mineralization using a self-organizing map
30. A comparative study of fuzzy weights of evidence and random forests for mapping mineral prospectivity for skarn-type Fe deposits in the southwestern Fujian metallogenic belt, China
31. The Behavior of Hydrothermal Mineralization With Spatial Variations of Fluid Pressure
32. Big Data Analytics of Identifying Geochemical Anomalies Supported by Machine Learning Methods
33. Recognition of geochemical anomalies using a deep autoencoder network
34. Revealing Geochemical Patterns Associated with Mineralization Using t-Distributed Stochastic Neighbor Embedding and Random Forest
35. A comparative study of fuzzy weights of evidence and random forests for mapping mineral prospectivity for skarn-type Fe deposits in the southwestern Fujian metallogenic belt, China
36. Mineral Prospectivity Mapping via Gated Recurrent Unit Model
37. A Physically Constrained Variational Autoencoder for Geochemical Pattern Recognition
38. The processing methods of geochemical exploration data: past, present, and future
39. Detection of geochemical anomalies related to mineralization using the GANomaly network
40. Detection of the multivariate geochemical anomalies associated with mineralization using a deep convolutional neural network and a pixel-pair feature method
41. Recognizing multivariate geochemical anomalies for mineral exploration by combining deep learning and one-class support vector machine
42. Robust Feature Extraction for Geochemical Anomaly Recognition Using a Stacked Convolutional Denoising Autoencoder
43. Recognition of geochemical anomalies using a deep variational autoencoder network
44. Random-Drop Data Augmentation of Deep Convolutional Neural Network for Mineral Prospectivity Mapping
45. Modeling singular mineralization processes due to fluid pressure fluctuations
46. Modelling the Singular Mineralization Process due to Fluid Pressure Fluctuations
47. GIS-based rare events logistic regression for mineral prospectivity mapping
48. A fractal model of granitic intrusion and variability based on cellular automata
49. Mapping Mineral Prospectivity via Semi-supervised Random Forest
50. Effects of misclassification costs on mapping mineral prospectivity
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