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"

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Title
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 26 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 42 12 0 10 Oct 2022
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 34 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 42 20 0 03 Sep 2022
Learning an Interpretable Model for Driver Behavior Prediction with Inductive Biases Salar Arbabi D. Tavernini Saber Fallah Richard Bowden 32 7 0 31 Jul 2022
Automated discovery of interpretable gravitational-wave population models Kaze W. K. Wong M. Cranmer 17 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 22 26 0 11 Jul 2022
Lagrangian Density Space-Time Deep Neural Network Topology B. Bishnoi PINN 25 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 14 0 29 May 2022
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions Fang Wu Siyuan Li Lirong Wu Dragomir R. Radev Stan Z. Li 27 2 0 15 May 2022
Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials Xiaolong He Jiun-Shyan Chen AI4CE 40 48 0 01 May 2022
Taylor Genetic Programming for Symbolic Regression Baihe He Qiang Lu Qingyun Yang Jake Luo Zhiguang Wang 37 29 0 28 Apr 2022
gLaSDI: Parametric Physics-informed Greedy Latent Space Dynamics Identification Xiaolong He Youngsoo Choi William D. Fries Jonathan Belof Jiun-Shyan Chen AI4CE 19 36 0 26 Apr 2022
End-to-end symbolic regression with transformers Pierre-Alexandre Kamienny Stéphane dÁscoli Guillaume Lample Franccois Charton 33 166 0 22 Apr 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
On scientific understanding with artificial intelligence Mario Krenn R. Pollice S. Guo Matteo Aldeghi Alba Cervera-Lierta ... Florian Hase A. Jinich AkshatKumar Nigam Zhenpeng Yao Alán Aspuru-Guzik 35 186 0 04 Apr 2022
Dimensionless machine learning: Imposing exact units equivariance Soledad Villar Weichi Yao D. Hogg Ben Blum-Smith Bianca Dumitrascu 23 26 0 02 Apr 2022
SELFIES and the future of molecular string representations Mario Krenn Qianxiang Ai Senja Barthel Nessa Carson Angelo Frei ... Andrew Wang Andrew D. White Adamo Young Rose Yu A. Aspuru‐Guzik 38 149 0 31 Mar 2022
Machine Learning and Cosmology C. Dvorkin S. Mishra-Sharma Brian D. Nord V. A. Villar Camille Avestruz ... A. Ćiprijanović Andrew J. Connolly L. Garrison G. Narayan F. Villaescusa-Navarro AI4CE 29 12 0 15 Mar 2022
Simulating Liquids with Graph Networks Jonathan Klimesch Philipp Holl Nils Thuerey GNN AI4CE 27 8 0 14 Mar 2022
Symbolic Learning to Optimize: Towards Interpretability and Scalability Wenqing Zheng Tianlong Chen Ting-Kuei Hu Zhangyang Wang 45 19 0 13 Mar 2022
Thermodynamics-informed graph neural networks Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto AI4CE PINN 32 31 0 03 Mar 2022
Evolving symbolic density functionals He Ma Arunachalam Narayanaswamy Patrick F. Riley Li Li 26 31 0 03 Mar 2022
Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting Lin Huang Lijun Wu Jia Zhang Jiang Bian Tie-Yan Liu AI4TS 34 2 0 18 Feb 2022
Forecasting Global Weather with Graph Neural Networks R. Keisler AI4Cl 33 166 0 15 Feb 2022
Learning Mechanically Driven Emergent Behavior with Message Passing Neural Networks Peerasait Prachaseree Emma Lejeune PINN AI4CE 33 11 0 03 Feb 2022
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism Siqi Miao Miaoyuan Liu Pan Li 18 197 0 31 Jan 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao Sun AI4CE 43 28 0 28 Jan 2022
Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately A. Sosanya S. Greydanus PINN AI4CE 44 28 0 25 Jan 2022
Flexible Networks for Learning Physical Dynamics of Deformable Objects Jinhyung D. Park Dohae Lee In-Kwon Lee 3DPC AI4CE 33 2 0 07 Dec 2021
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 75 26 0 06 Dec 2021
Hamiltonian latent operators for content and motion disentanglement in image sequences Asif Khan Amos Storkey 29 2 0 02 Dec 2021
From Kepler to Newton: Explainable AI for Science Zelong Li Jianchao Ji Yongfeng Zhang 26 19 0 24 Nov 2021
Physics-enhanced deep surrogates for partial differential equations R. Pestourie Youssef Mroueh Chris Rackauckas Payel Das Steven G. Johnson PINN AI4CE 25 15 0 10 Nov 2021
Discovering Latent Representations of Relations for Interacting Systems Dohae Lee Young-Jin Oh In-Kwon Lee BDL 27 1 0 10 Nov 2021
Chaos as an interpretable benchmark for forecasting and data-driven modelling W. Gilpin AI4TS 27 76 0 11 Oct 2021
Lagrangian Neural Network with Differentiable Symmetries and Relational Inductive Bias Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 55 4 0 07 Oct 2021
Interpretable deep-learning models to help achieve the Sustainable Development Goals Ricardo Vinuesa B. Sirmaçek 16 84 0 24 Aug 2021
An Extensible Benchmark Suite for Learning to Simulate Physical Systems Karl Otness Arvi Gjoka Joan Bruna Daniele Panozzo Benjamin Peherstorfer T. Schneider Denis Zorin 24 23 0 09 Aug 2021
DySMHO: Data-Driven Discovery of Governing Equations for Dynamical Systems via Moving Horizon Optimization F. Lejarza M. Baldea AI4CE 27 38 0 30 Jul 2021
Reasoning-Modulated Representations Petar Velivcković Matko Bovsnjak Thomas Kipf Alexander Lerchner R. Hadsell Razvan Pascanu Charles Blundell OCL OOD SSL 18 15 0 19 Jul 2021
Unsupervised Resource Allocation with Graph Neural Networks M. Cranmer Peter Melchior Brian D. Nord 21 12 0 17 Jun 2021
Neural Symbolic Regression that Scales Luca Biggio Tommaso Bendinelli Alexander Neitz Aurelien Lucchi Giambattista Parascandolo 54 170 0 11 Jun 2021
Neuro-Symbolic Artificial Intelligence: Current Trends Md Kamruzzaman Sarker Lu Zhou Aaron Eberhart Pascal Hitzler NAI 27 87 0 11 May 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure Samuel Kim Peter Y. Lu Charlotte Loh Jamie Smith Jasper Snoek M. Soljavcić BDL AI4CE 136 17 0 23 Apr 2021
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution Omer San Adil Rasheed T. Kvamsdal 48 50 0 26 Mar 2021
Utilising Graph Machine Learning within Drug Discovery and Development Thomas Gaudelet Ben Day Arian R. Jamasb Jyothish Soman Cristian Regep ... Jian Tang D. Roblin Tom L. Blundell M. Bronstein J. Taylor-King AI4CE 29 36 0 09 Dec 2020
Disentangling a Deep Learned Volume Formula J. Craven Vishnu Jejjala Arjun Kar 13 19 0 07 Dec 2020
Reverse engineering learned optimizers reveals known and novel mechanisms Niru Maheswaranathan David Sussillo Luke Metz Ruoxi Sun Jascha Narain Sohl-Dickstein 22 21 0 04 Nov 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 139 425 0 10 Mar 2020