GiorgioML
  • Bio
  • Papers
  • Experience
  • Talks
  • Recent News
  • Blog
  • Blog
    • I've got a workshop paper accepted at EurIPS 2025
    • I defended my PhD thesis
    • I received the Gianforte School of Computing's "Outstanding PhD Researcher" Award
    • I received MSU's "Everyday Hero of Research" Award
    • Our J2C presentation was accepted at IJCNN 2025
    • Our AAAI paper was presented in Philadelphia today
    • Blog post - Diffusion Models Background
    • I've got a paper accepted at AAAI 2025
    • Blog post - Score matching for score estimation
    • Interview with MSU's News
    • Blog post - Unraveling the Complexity of Multivariate Systems with Symbolic Regression
    • I won the first place in the SMAC competition at ECML PKDD 2024
    • Our IJCNN paper was presented in Yokohama today
    • My work was accepted for presentation at the ECML PKDD PhD Forum
    • I've got a paper accepted at ECML PKDD 2024
    • I've got a paper accepted at IJCNN 2024
    • Blog post - Prediction Intervals Generation in Python
    • I've got a journal paper accepted at IEEE TNNLS
    • I received the Chunzi "Chris" Zhang Award
    • Interview with MSU's Graduate School
    • On-Field Precision Experiment (OFPE) Framework project
    • Blog post - Best hyperspectral bands for Indian-Pines and Salinas datasets
    • Blog post - Linear Regression in PyTorch
    • Blog post - Layer-wise Relevance Propagation in PyTorch
  • Publications
    • Towards Uncertainty Quantification in Generative Model Learning
    • Decomposable Neuro Symbolic Regression
    • Adaptive Sampling to Reduce Epistemic Uncertainty Using Prediction Interval-Generation Neural Networks
    • Univariate Skeleton Prediction in Multivariate Systems Using Transformers
    • Counterfactual Analysis of Neural Networks Used to Create Fertilizer Management Zones
    • Counterfactual Explanations of Neural Network-Generated Response Curves
    • Dual Accuracy-Quality-Driven Neural Network for Prediction Interval Generation
    • Improved Yield Prediction of Winter Wheat Using a Novel Two-Dimensional Deep Regression Neural Network Trained via Remote Sensing
    • Decision Support From On-Field Precision Experiments
    • Generation of Site-specific Nitrogen Response Curves for Winter Wheat using Deep Learning
    • Optimizing Nitrogen Application to Maximize Yield and Reduce Environmental Impact in Winter Wheat Production
    • Two-dimensional deep regression for early yield prediction of winter wheat
    • Hyperspectral Band Selection for Multispectral Image Classification with Convolutional Networks
    • Hyperspectral Dimensionality Reduction Based on Inter-Band Redundancy Analysis and Greedy Spectral Selection
    • Towards reduced-cost hyperspectral and multispectral image classification
    • Reduced-cost hyperspectral convolutional neural networks
    • End-to-end Cloud Segmentation in High-Resolution Multispectral Satellite Imagery Using Deep Learning
    • Estimation of 2D Velocity Model using Acoustic Signals and Convolutional Neural Networks
    • Regression Models between Active Sensor-Measured NDVI and UAV-Acquired Multispectral Images with Positioning Uncertainty
    • Cloud Detection for PERUSAT-1 Imagery Using Spectral and Texture Descriptors, ANN, and Panchromatic Fusion
    • Detecting Violent Robberies in CCTV Videos Using Deep Learning
    • Shadow Removal in High-Resolution Satellite Images Using Conditional Generative Adversarial Networks
    • Automatic Segmentation of Mauritia flexuosa in Unmanned Aerial Vehicle (UAV) Imagery Using Deep Learning
    • PETEFA: Geographic Information System for Precision Agriculture
    • Shadow Detection in High-Resolution Multispectral Satellite Imagery Using Generative Adversarial Networks
    • Cloud Detection in High-Resolution Multispectral Satellite Imagery Using Deep Learning
  • Recent & Upcoming Talks
    • Trustworthy AI Seminar at UPV
    • Presentation at DIGICROP 2025
    • Managing Uncertainty in Regression Neural Networks - From Prediction Intervals to Adaptive Sampling
    • Decomposable Symbolic Regression Using Transformers and Neural Network-Assisted Genetic Algorithms
    • AI for Precision Agiculture
    • Presentations at ECML-PKDD 2024
    • Counterfactual Explanations of Nitrogen Response Curves
    • Prediction Software using OFPE and Machine Learning
  • About
  • Projects
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Experience
  • Teaching
    • Learn JavaScript
    • Learn Python

Decomposable Neuro Symbolic Regression

Nov 6, 2025·
Giorgio Morales
,
John W. Sheppard
· 0 min read
Cite arXiv URL
Type
Manuscript
Last updated on Nov 6, 2025
Symbolic Regression XAI Transformers Knowledge Discovery
← Towards Uncertainty Quantification in Generative Model Learning Nov 12, 2025
Adaptive Sampling to Reduce Epistemic Uncertainty Using Prediction Interval-Generation Neural Networks Feb 10, 2025 →

© 2025 Me. This work is licensed under CC BY NC ND 4.0

Published with Hugo Blox Builder — the free, open source website builder that empowers creators.