Interpretable Scientific Discovery with Symbolic Regression: A Review
Fuente:
arXiv
Saved in:
| Main Authors: | Makke, Nour, Chawla, Sanjay |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Inferring Interpretable Models of Fragmentation Functions using Symbolic Regression
by: Makke, Nour, et al.
Published: (2025)
by: Makke, Nour, et al.
Published: (2025)
A Perspective on Symbolic Machine Learning in Physical Sciences
by: Makke, Nour, et al.
Published: (2025)
by: Makke, Nour, et al.
Published: (2025)
Symbolic Regression for Beyond the Standard Model Physics
by: AbdusSalam, Shehu, et al.
Published: (2024)
by: AbdusSalam, Shehu, et al.
Published: (2024)
Iterated Agent for Symbolic Regression
by: Song, Zhuo-Yang, et al.
Published: (2025)
by: Song, Zhuo-Yang, et al.
Published: (2025)
Symbolic Regression and Differentiable Fits in Beyond the Standard Model Physics
by: AbdusSalam, Shehu, et al.
Published: (2025)
by: AbdusSalam, Shehu, et al.
Published: (2025)
Agents of Discovery
by: Diefenbacher, Sascha, et al.
Published: (2025)
by: Diefenbacher, Sascha, et al.
Published: (2025)
Artificial Intelligence and Symmetries: Learning, Encoding, and Discovering Structure in Physical Data
by: Sanz, Veronica
Published: (2026)
by: Sanz, Veronica
Published: (2026)
Calibrating Bayesian Generative Machine Learning for Bayesiamplification
by: Bieringer, Sebastian, et al.
Published: (2024)
by: Bieringer, Sebastian, et al.
Published: (2024)
AI-Newton: A Concept-Driven Physical Law Discovery System without Prior Physical Knowledge
by: Fang, You-Le, et al.
Published: (2025)
by: Fang, You-Le, et al.
Published: (2025)
Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction
by: Faroughy, Darius A., et al.
Published: (2026)
by: Faroughy, Darius A., et al.
Published: (2026)
Learning Pole Structures of Hadronic States using Predictive Uncertainty Estimation
by: Frohnert, Felix, et al.
Published: (2025)
by: Frohnert, Felix, et al.
Published: (2025)
Improving Neutrino Oscillation Measurements through Event Classification
by: Ellis, Sebastian A. R., et al.
Published: (2025)
by: Ellis, Sebastian A. R., et al.
Published: (2025)
Fine-Tuning Small Reasoning Models for Quantum Field Theory
by: Woodward, Nathaniel S., et al.
Published: (2026)
by: Woodward, Nathaniel S., et al.
Published: (2026)
High-dimensional and Permutation Invariant Anomaly Detection
by: Mikuni, Vinicius, et al.
Published: (2023)
by: Mikuni, Vinicius, et al.
Published: (2023)
Uncovering Singularities in Feynman Integrals via Machine Learning
by: Liu, Yuanche, et al.
Published: (2025)
by: Liu, Yuanche, et al.
Published: (2025)
Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion
by: Shmakov, Alexander, et al.
Published: (2024)
by: Shmakov, Alexander, et al.
Published: (2024)
Generative Invertible Quantum Neural Networks
by: Rousselot, Armand, et al.
Published: (2023)
by: Rousselot, Armand, et al.
Published: (2023)
Uncertainty Quantification From Scaling Laws in Deep Neural Networks
by: Elsharkawy, Ibrahim, et al.
Published: (2025)
by: Elsharkawy, Ibrahim, et al.
Published: (2025)
Symbolic Density Estimation: A Decompositional Approach
by: Rajendram, Angelo, et al.
Published: (2026)
by: Rajendram, Angelo, et al.
Published: (2026)
Deep Generative Models for Ultra-High Granularity Particle Physics Detector Simulation: A Voyage From Emulation to Extrapolation
by: Hashemi, Baran
Published: (2024)
by: Hashemi, Baran
Published: (2024)
A Step Toward Interpretability: Smearing the Likelihood
by: Larkoski, Andrew J.
Published: (2025)
by: Larkoski, Andrew J.
Published: (2025)
Test-time Scaling Techniques in Theoretical Physics -- A Comparison of Methods on the TPBench Dataset
by: Gao, Zhiqi, et al.
Published: (2025)
by: Gao, Zhiqi, et al.
Published: (2025)
Angular Coefficients from Interpretable Machine Learning with Symbolic Regression
by: Bendavid, Josh, et al.
Published: (2025)
by: Bendavid, Josh, et al.
Published: (2025)
Bumblebee: Foundation Model for Particle Physics Discovery
by: Wildridge, Andrew J., et al.
Published: (2024)
by: Wildridge, Andrew J., et al.
Published: (2024)
Zephyr quantum-assisted hierarchical Calo4pQVAE for particle-calorimeter interactions
by: Lu, Ian, et al.
Published: (2024)
by: Lu, Ian, et al.
Published: (2024)
Theoretical Physics Benchmark (TPBench) -- a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics
by: Chung, Daniel J. H., et al.
Published: (2025)
by: Chung, Daniel J. H., et al.
Published: (2025)
Dissecting Jet-Tagger Through Mechanistic Interpretability
by: Rai, Saurabh, et al.
Published: (2026)
by: Rai, Saurabh, et al.
Published: (2026)
Mixture-of-Experts Graph Transformers for Interpretable Particle Collision Detection
by: Genovese, Donatella, et al.
Published: (2025)
by: Genovese, Donatella, et al.
Published: (2025)
Stable and Interpretable Jet Physics with IRC-Safe Equivariant Feature Extraction
by: Konar, Partha, et al.
Published: (2025)
by: Konar, Partha, et al.
Published: (2025)
Conditioned quantum-assisted deep generative surrogate for particle-calorimeter interactions
by: Toledo-Marin, J. Quetzalcoatl, et al.
Published: (2024)
by: Toledo-Marin, J. Quetzalcoatl, et al.
Published: (2024)
Improving robustness of jet tagging algorithms with adversarial training: exploring the loss surface
by: Stein, Annika
Published: (2023)
by: Stein, Annika
Published: (2023)
Foundation models for high-energy physics
by: Hallin, Anna
Published: (2025)
by: Hallin, Anna
Published: (2025)
Jet Image Tagging Using Deep Learning: An Ensemble Model
by: Bassa, Juvenal, et al.
Published: (2025)
by: Bassa, Juvenal, et al.
Published: (2025)
Scalable Quantum State Preparation via Large-Language-Model-Driven Discovery
by: Cao, Qing-Hong, et al.
Published: (2025)
by: Cao, Qing-Hong, et al.
Published: (2025)
$\mathcal{CP}$-Analyses with Symbolic Regression
by: Bahl, Henning, et al.
Published: (2025)
by: Bahl, Henning, et al.
Published: (2025)
Learning to Unscramble: Simplifying Symbolic Expressions via Self-Supervised Oracle Trajectories
by: Shih, David
Published: (2026)
by: Shih, David
Published: (2026)
Jet Image Generation in High Energy Physics Using Diffusion Models
by: Martinez, Victor D., et al.
Published: (2025)
by: Martinez, Victor D., et al.
Published: (2025)
Generalized Parton Distributions from Symbolic Regression
by: Dotson, Andrew, et al.
Published: (2025)
by: Dotson, Andrew, et al.
Published: (2025)
Xiwu: A Basis Flexible and Learnable LLM for High Energy Physics
by: Zhang, Zhengde, et al.
Published: (2024)
by: Zhang, Zhengde, et al.
Published: (2024)
Folded Context Condensation in Path Integral Formalism for Infinite Context Transformers
by: Paeng, Won-Gi, et al.
Published: (2024)
by: Paeng, Won-Gi, et al.
Published: (2024)
Similar Items
-
Inferring Interpretable Models of Fragmentation Functions using Symbolic Regression
by: Makke, Nour, et al.
Published: (2025) -
A Perspective on Symbolic Machine Learning in Physical Sciences
by: Makke, Nour, et al.
Published: (2025) -
Symbolic Regression for Beyond the Standard Model Physics
by: AbdusSalam, Shehu, et al.
Published: (2024) -
Iterated Agent for Symbolic Regression
by: Song, Zhuo-Yang, et al.
Published: (2025) -
Symbolic Regression and Differentiable Fits in Beyond the Standard Model Physics
by: AbdusSalam, Shehu, et al.
Published: (2025)