Discovering Symbolic Models from Deep Learning with Inductive Biases

19 June 2020

M. Cranmer

Alvaro Sanchez-Gonzalez

Papers citing "Discovering Symbolic Models from Deep Learning with Inductive Biases"

50 / 78 papers shown

Title
Compression, Regularity, Randomness and Emergent Structure: Rethinking Physical Complexity in the Data-Driven Era Nima Dehghani AI4CE 24 0 0 12 May 2025
Identifying Unknown Stochastic Dynamics via Finite expression methods Senwei Liang Chunmei Wang Xingjian Xu 21 0 0 09 Apr 2025
Learning Epidemiological Dynamics via the Finite Expression Method Jianda Du Senwei Liang Chunmei Wang 36 1 0 31 Dec 2024
Closed-Form Interpretation of Neural Network Latent Spaces with Symbolic Gradients Zakaria Patel S. J. Wetzel 18 2 0 09 Sep 2024
Decomposing heterogeneous dynamical systems with graph neural networks Cédric Allier Magdalena C. Schneider Michael Innerberger Larissa Heinrich J. Bogovic S. Saalfeld CML AI4CE 30 0 0 27 Jul 2024
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos P. Koutsourelakis AI4CE 29 3 0 29 May 2024
Symbolic Regression for Beyond the Standard Model Physics Shehu AbdusSalam Steve Abel M. Romão 18 5 0 28 May 2024
ISR: Invertible Symbolic Regression Tony Tohme M. J. Khojasteh Mohsen Sadr Florian Meyer Kamal Youcef-Toumi 43 0 0 10 May 2024
Classical integrability in the presence of a cosmological constant: analytic and machine learning results G. L. Cardoso D. M. Pena S. Nampuri 22 2 0 28 Apr 2024
Opening the AI black box: program synthesis via mechanistic interpretability Eric J. Michaud Isaac Liao Vedang Lad Ziming Liu Anish Mudide Chloe Loughridge Zifan Carl Guo Tara Rezaei Kheirkhah Mateja Vukelić Max Tegmark 23 12 0 07 Feb 2024
Vertical Symbolic Regression Nan Jiang Md Nasim Yexiang Xue 16 1 0 19 Dec 2023
Machine-Guided Discovery of a Real-World Rogue Wave Model Dion Häfner Johannes Gemmrich Markus Jochum AI4CE 11 10 0 21 Nov 2023
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 18 9 0 08 Oct 2023
Worrisome Properties of Neural Network Controllers and Their Symbolic Representations J. Cyranka Kevin E. M. Church J. Lessard 26 0 0 28 Jul 2023
Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks S. Bishnoi Ravinder Bhattoo J. Jayadeva Sayan Ranu N. M. A. Krishnan PINN AI4CE 26 1 0 11 Jul 2023
Supervised Attention Using Homophily in Graph Neural Networks Michail Chatzianastasis Giannis Nikolentzos Michalis Vazirgiannis GNN 11 0 0 11 Jul 2023
MESSY Estimation: Maximum-Entropy based Stochastic and Symbolic densitY Estimation Tony Tohme Mohsen Sadr K. Youcef-Toumi N. Hadjiconstantinou 30 3 0 07 Jun 2023
Discovering Causal Relations and Equations from Data Gustau Camps-Valls Andreas Gerhardus Urmi Ninad Gherardo Varando Georg Martius E. Balaguer-Ballester Ricardo Vinuesa Emiliano Díaz L. Zanna Jakob Runge PINN AI4Cl AI4CE CML 35 72 0 21 May 2023
Seeing is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability Ziming Liu Eric Gan Max Tegmark 13 36 0 04 May 2023
Differentiable Genetic Programming for High-dimensional Symbolic Regression Peng Zeng Xiaotian Song Andrew Lensen Yuwei Ou Yanan Sun Mengjie Zhang Jiancheng Lv 18 2 0 18 Apr 2023
Priors for symbolic regression Deaglan J. Bartlett Harry Desmond Pedro G. Ferreira 29 5 0 13 Apr 2023
On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods Artur P. Toshev Ludger Paehler A. Panizza Nikolaus A. Adams AI4CE PINN 11 5 0 31 Mar 2023
Machine Learning for Partial Differential Equations Steven L. Brunton J. Nathan Kutz AI4CE 29 20 0 30 Mar 2023
The transformative potential of machine learning for experiments in fluid mechanics Ricardo Vinuesa Steven L. Brunton B. McKeon AI4CE 19 68 0 28 Mar 2023
MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning S Chandra Mouli M. A. Alam Bruno Ribeiro OOD 15 4 0 06 Mar 2023
Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook Xuan Di Rongye Shi Zhaobin Mo Yongjie Fu PINN AI4TS AI4CE 24 28 0 03 Mar 2023
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search Pierre-Alexandre Kamienny Guillaume Lample Sylvain Lamprier M. Virgolin 21 25 0 22 Feb 2023
Oracle-Preserving Latent Flows Alexander Roman Roy T. Forestano Konstantin T. Matchev Katia Matcheva Eyup B. Unlu DRL 24 5 0 02 Feb 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 24 5 0 26 Jan 2023
Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles Roy T. Forestano Konstantin T. Matchev Katia Matcheva Alexander Roman Eyup B. Unlu Sarunas Verner AI4CE 28 21 0 13 Jan 2023
Neural Spline Search for Quantile Probabilistic Modeling Ruoxi Sun Chun-Liang Li Sercan Ö. Arik Michael W. Dusenberry Chen-Yu Lee Tomas Pfister AI4TS 38 5 0 12 Jan 2023
Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search Wenqing Zheng S. Sharan Zhiwen Fan Kevin Wang Yihan Xi Zhangyang Wang 53 9 0 30 Dec 2022
Renormalization in the neural network-quantum field theory correspondence Harold Erbin Vincent Lahoche D. O. Samary 24 7 0 22 Dec 2022
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection Benjamin Steenhoek Hongyang Gao Wei Le 27 27 0 15 Dec 2022
Emerging trends in machine learning for computational fluid dynamics Ricardo Vinuesa Steve Brunton AI4CE 14 14 0 28 Nov 2022
Certified data-driven physics-informed greedy auto-encoder simulator Xiaolong He Youngsoo Choi William D. Fries Jonathan Belof Jiun-Shyan Chen AI4CE 11 2 0 24 Nov 2022
Interpretable Scientific Discovery with Symbolic Regression: A Review N. Makke S. Chawla 19 92 0 20 Nov 2022
Is the Machine Smarter than the Theorist: Deriving Formulas for Particle Kinematics with Symbolic Regression Zhongtian Dong K. Kong Konstantin T. Matchev Katia Matcheva 38 13 0 15 Nov 2022
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems A. Thangamuthu Gunjan Kumar S. Bishnoi Ravinder Bhattoo N. M. A. Krishnan Sayan Ranu AI4CE PINN 27 22 0 10 Nov 2022
Simulation-Based Parallel Training Lucas Meyer Alejandro Ribés Bruno Raffin AI4CE 23 2 0 08 Nov 2022
Symbolic Distillation for Learned TCP Congestion Control S. Sharan Wenqing Zheng Kuo-Feng Hsu Jiarong Xing Ang Chen Zhangyang Wang 15 5 0 24 Oct 2022
How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization Jonas Geiping Micah Goldblum Gowthami Somepalli Ravid Shwartz-Ziv Tom Goldstein A. Wilson 21 35 0 12 Oct 2022
Neurosymbolic Programming for Science Jennifer J. Sun Megan Tjandrasuwita Atharva Sehgal Armando Solar-Lezama Swarat Chaudhuri Yisong Yue Omar Costilla-Reyes NAI 35 12 0 10 Oct 2022
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 26 17 0 23 Sep 2022
Learning the Dynamics of Particle-based Systems with Lagrangian Graph Neural Networks Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan PINN AI4CE 21 20 0 03 Sep 2022
Learning an Interpretable Model for Driver Behavior Prediction with Inductive Biases Salar Arbabi D. Tavernini Saber Fallah Richard Bowden 20 6 0 31 Jul 2022
Automated discovery of interpretable gravitational-wave population models Kaze W. K. Wong M. Cranmer 12 7 0 25 Jul 2022
The Cosmic Graph: Optimal Information Extraction from Large-Scale Structure using Catalogues T. Lucas Makinen Tom Charnock Pablo Lemos Natalia Porqueres A. Heavens Benjamin Dan Wandelt 20 26 0 11 Jul 2022
Lagrangian Density Space-Time Deep Neural Network Topology B. Bishnoi PINN 15 1 0 30 Jun 2022
Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs) J. Abbasi Paal Ostebo Andersen PINN AI4CE 25 13 0 29 May 2022