Learning Equations for Extrapolation and Control

19 June 2018

Papers citing "Learning Equations for Extrapolation and Control"

39 / 39 papers shown

Title
Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics Conor F. Hayes Felipe Leno Da Silva Jiachen Yang T. Nathan Mundhenk Chak Shing Lee ... Ahmet Can Solak Thomas Desautels Daniel Faissol Brenden K. Petersen Mikel Landajuela 14 0 0 16 May 2025
Feasibility-Aware Pessimistic Estimation: Toward Long-Horizon Safety in Offline RL Zhikun Tao Gang Xiong He Fang Zhen Shen Yunjun Han Qing-Shan Jia OffRL 34 0 0 13 May 2025
UniSymNet: A Unified Symbolic Network Guided by Transformer Xinxin Li Juan Zhang Da Li Xingyu Liu Jin Xu Junping Yin 34 0 0 09 May 2025
Hadamard product in deep learning: Introduction, Advances and Challenges Grigorios G. Chrysos Yongtao Wu Razvan Pascanu Philip Torr V. Cevher AAML 98 0 0 17 Apr 2025
Evolving Form and Function: Dual-Objective Optimization in Neural Symbolic Regression Networks Amanda Bertschinger James P. Bagrow Joshua Bongard 90 1 0 24 Feb 2025
No Equations Needed: Learning System Dynamics Without Relying on Closed-Form ODEs Krzysztof Kacprzyk M. Schaar 114 0 0 30 Jan 2025
Generalizing the SINDy approach with nested neural networks Camilla Fiorini Clément Flint Louis Fostier Emmanuel Franck Reyhaneh Hashemi Victor Michel-Dansac Wassim Tenachi 76 1 0 28 Jan 2025
Closed-Form Interpretation of Neural Network Latent Spaces with Symbolic Gradients Zakaria Patel S. J. Wetzel 23 2 0 09 Sep 2024
ISR: Invertible Symbolic Regression Tony Tohme M. J. Khojasteh Mohsen Sadr Florian Meyer Kamal Youcef-Toumi 51 0 0 10 May 2024
PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression Min Wu Weijun Li Lina Yu Wenqiang Li Jingyi Liu Yanjie Li Meilan Hao 20 1 0 25 Jan 2024
ParFam -- (Neural Guided) Symbolic Regression Based on Continuous Global Optimization Philipp Scholl Katharina Bieker Hillary Hauger Gitta Kutyniok 43 4 0 09 Oct 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 20 10 0 08 Oct 2023
StreamBed: capacity planning for stream processing Guillaume Rosinosky Donatien Schmitz Etienne Rivière 17 3 0 06 Sep 2023
Probabilistic Regular Tree Priors for Scientific Symbolic Reasoning Tim Schneider A. Totounferoush Wolfgang Nowak Steffen Staab 23 0 0 14 Jun 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
Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning Shuo Yu Hongyan Xue Xiang Ao Feiyang Pan Jia He Dandan Tu Qing He AIFin 32 11 0 25 May 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
Differentiable Genetic Programming for High-dimensional Symbolic Regression Peng Zeng Xiaotian Song Andrew Lensen Yuwei Ou Yanan Sun Mengjie Zhang Jiancheng Lv 34 2 0 18 Apr 2023
Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications N. Ranasinghe A. Ramanan S. Fernando P. N. Hameed D. Herath T. Malepathirana P. Suganthan M. Niranjan Saman K. Halgamuge 8 2 0 30 Nov 2022
Interpretable Scientific Discovery with Symbolic Regression: A Review N. Makke S. Chawla 38 93 0 20 Nov 2022
Discovering ordinary differential equations that govern time-series Soren Becker M. Klein Alexander Neitz Giambattista Parascandolo Niki Kilbertus AI4TS 24 4 0 05 Nov 2022
DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learning Mengge Du Yuntian Chen Dong-juan Zhang 33 0 0 04 Oct 2022
From Perception to Programs: Regularize, Overparameterize, and Amortize Hao Tang Kevin Ellis NAI 22 10 0 13 Jun 2022
Taylor Genetic Programming for Symbolic Regression Baihe He Qiang Lu Qingyun Yang Jake Luo Zhiguang Wang 34 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 25 163 0 22 Apr 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao Sun AI4CE 43 27 0 28 Jan 2022
Deep Symbolic Regression for Recurrent Sequences Stéphane dÁscoli Pierre-Alexandre Kamienny Guillaume Lample Franccois Charton 47 54 0 12 Jan 2022
Symbolic Regression via Neural-Guided Genetic Programming Population Seeding T. Nathan Mundhenk Mikel Landajuela Ruben Glatt Claudio Santiago Daniel Faissol Brenden K. Petersen 32 85 0 29 Oct 2021
Learning Division with Neural Arithmetic Logic Modules Bhumika Mistry K. Farrahi Jonathon S. Hare 20 0 0 11 Oct 2021
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling Kookjin Lee Nathaniel Trask P. Stinis 35 25 0 11 Sep 2021
Contemporary Symbolic Regression Methods and their Relative Performance William La Cava Patryk Orzechowski Bogdan Burlacu Fabrício Olivetti de Francca M. Virgolin Ying Jin M. Kommenda J. Moore 44 249 0 29 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 65 0 02 Jul 2021
SymbolicGPT: A Generative Transformer Model for Symbolic Regression Mojtaba Valipour Bowen You Maysum Panju A. Ghodsi 16 88 0 27 Jun 2021
Neural Symbolic Regression that Scales Luca Biggio Tommaso Bendinelli Alexander Neitz Aurelien Lucchi Giambattista Parascandolo 45 170 0 11 Jun 2021
Symbolically Solving Partial Differential Equations using Deep Learning Maysum Panju Kourosh Parand A. Ghodsi 8 3 0 12 Nov 2020
Implicit Neural Representations with Periodic Activation Functions Vincent Sitzmann Julien N. P. Martel Alexander W. Bergman David B. Lindell Gordon Wetzstein AI4TS 44 2,486 0 17 Jun 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 2020
PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network Zichao Long Yiping Lu Bin Dong AI4CE 31 542 0 30 Nov 2018