Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2401.09949
Cited By
v1
v2
v3 (latest)
SymbolNet: Neural Symbolic Regression with Adaptive Dynamic Pruning for Compression
18 January 2024
Ho Fung Tsoi
Vladimir Loncar
S. Dasu
Philip C. Harris
Re-assign community
ArXiv (abs)
PDF
HTML
Github (7★)
Papers citing
"SymbolNet: Neural Symbolic Regression with Adaptive Dynamic Pruning for Compression"
35 / 35 papers shown
hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware
Jan-Frederik Schulte
Benjamin Ramhorst
Chang Sun
Jovan Mitrevski
Nicolò Ghielmetti
...
C. Herwig
Ho Fung Tsoi
D. Rankin
Shih-Chieh Hsu
Scott Hauck
VLM
173
3
0
01 Dec 2025
Decomposable Neuro Symbolic Regression
Giorgio Morales
John W. Sheppard
156
0
0
06 Nov 2025
Discovering Nuclear Models from Symbolic Machine Learning
Jose M. Munoz
S. Udrescu
Ronald F. Garcia Ruiz
327
4
0
17 Apr 2024
Symbolic Regression on FPGAs for Fast Machine Learning Inference
EPJ Web of Conferences (EPJ Web Conf.), 2023
Ho Fung Tsoi
Adrian Alan Pol
Vladimir Loncar
E. Govorkova
M. Cranmer
S. Dasu
P. Elmer
Philip C. Harris
I. Ojalvo
M. Pierini
291
17
0
06 May 2023
Differentiable Genetic Programming for High-dimensional Symbolic Regression
Peng Zeng
Xiaotian Song
Andrew Lensen
Yuwei Ou
Yanan Sun
Mengjie Zhang
Jiancheng Lv
215
4
0
18 Apr 2023
Toward Physically Plausible Data-Driven Models: A Novel Neural Network Approach to Symbolic Regression
IEEE Access (IEEE Access), 2023
Jiří Kubalík
Erik Derner
Robert Babuška
271
20
0
01 Feb 2023
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization
International Conference/Workshop on Computer Aided Systems Theory (EUROCAST), 2022
Lukas Kammerer
G. Kronberger
M. Kommenda
237
5
0
20 Sep 2022
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge
Scientific Reports (Sci Rep), 2022
Liron Simon Keren
A. Liberzon
Teddy Lazebnik
357
102
0
13 Sep 2022
The SZ flux-mass (
Y
Y
Y
-
M
M
M
) relation at low halo masses: improvements with symbolic regression and strong constraints on baryonic feedback
Monthly notices of the Royal Astronomical Society (MNRAS), 2022
D. Wadekar
L. Thiele
J. Hill
S. Pandey
F. Villaescusa-Navarro
...
M. Cranmer
D. Nagai
D. Anglés-Alcázar
S. Ho
L. Hernquist
AI4CE
181
22
0
05 Sep 2022
Symbolic Regression is NP-hard
M. Virgolin
S. Pissis
540
95
0
03 Jul 2022
Bayesian Learning to Discover Mathematical Operations in Governing Equations of Dynamic Systems
Hongpeng Zhou
W. Pan
222
6
0
01 Jun 2022
SymFormer: End-to-end symbolic regression using transformer-based architecture
IEEE Access (IEEE Access), 2022
Martin Vastl
Jonáš Kulhánek
Jiří Kubalík
Erik Derner
Robert Babuška
503
87
0
31 May 2022
End-to-end symbolic regression with transformers
Neural Information Processing Systems (NeurIPS), 2022
Pierre-Alexandre Kamienny
Stéphane dÁscoli
Guillaume Lample
Franccois Charton
344
266
0
22 Apr 2022
Rediscovering orbital mechanics with machine learning
Pablo Lemos
N. Jeffrey
M. Cranmer
S. Ho
Peter W. Battaglia
PINN
AI4CE
358
130
0
04 Feb 2022
Augmenting astrophysical scaling relations with machine learning: application to reducing the Sunyaev-Zeldovich flux-mass scatter
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2022
D. Wadekar
L. Thiele
F. Villaescusa-Navarro
J. Hill
M. Cranmer
D. Spergel
N. Battaglia
D. Anglés-Alcázar
L. Hernquist
S. Ho
529
16
0
04 Jan 2022
PySINDy: A comprehensive Python package for robust sparse system identification
Journal of Open Source Software (JOSS), 2021
A. Kaptanoglu
Brian M. de Silva
Urban Fasel
Kadierdan Kaheman
Andy J. Goldschmidt
...
Zachary G. Nicolaou
Kathleen P. Champion
Jean-Christophe Loiseau
J. Nathan Kutz
Steven L. Brunton
AI4CE
403
220
0
12 Nov 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
459
375
0
29 Jul 2021
SymbolicGPT: A Generative Transformer Model for Symbolic Regression
Mojtaba Valipour
Bowen You
Maysum Panju
A. Ghodsi
198
125
0
27 Jun 2021
Neural Symbolic Regression that Scales
International Conference on Machine Learning (ICML), 2021
Luca Biggio
Tommaso Bendinelli
Alexander Neitz
Aurelien Lucchi
Giambattista Parascandolo
262
246
0
11 Jun 2021
Informed Equation Learning
M. Werner
Andrej Junginger
Philipp Hennig
Georg Martius
213
20
0
13 May 2021
Symbolic regression for scientific discovery: an application to wind speed forecasting
IEEE Symposium Series on Computational Intelligence (SSCI), 2021
Ismail Alaoui Abdellaoui
S. Mehrkanoon
216
28
0
21 Feb 2021
Fast convolutional neural networks on FPGAs with hls4ml
T. Aarrestad
Vladimir Loncar
Nicolò Ghielmetti
M. Pierini
S. Summers
...
N. Tran
Miaoyuan Liu
E. Kreinar
Zhenbin Wu
Duc Hoang
236
153
0
13 Jan 2021
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors
C. Coelho
Aki Kuusela
Shane Li
Zhuang Hao
T. Aarrestad
Vladimir Loncar
J. Ngadiuba
M. Pierini
Adrian Alan Pol
S. Summers
MQ
360
231
0
15 Jun 2020
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers
Junjie Liu
Zhe Xu
Runbin Shi
R. Cheung
Hayden Kwok-Hay So
279
135
0
14 May 2020
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
International Conference on Learning Representations (ICLR), 2019
Brenden K. Petersen
Mikel Landajuela
T. Nathan Mundhenk
Claudio Santiago
Soo K. Kim
Joanne T. Kim
593
435
0
10 Dec 2019
Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019
Samuel Kim
Peter Y. Lu
Srijon Mukherjee
M. Gilbert
Li Jing
V. Ceperic
Marin Soljacic
261
223
0
10 Dec 2019
AI Feynman: a Physics-Inspired Method for Symbolic Regression
Science Advances (Sci Adv), 2019
S. Udrescu
Max Tegmark
670
1,176
0
27 May 2019
Learning Equations for Extrapolation and Control
Subham S. Sahoo
Christoph H. Lampert
Georg Martius
258
283
0
19 Jun 2018
Fast inference of deep neural networks in FPGAs for particle physics
Javier Mauricio Duarte
Song Han
Philip C. Harris
S. Jindariani
E. Kreinar
...
J. Ngadiuba
M. Pierini
R. Rivera
N. Tran
Zhenbin Wu
AI4CE
439
481
0
16 Apr 2018
Learning Sparse Neural Networks through
L
0
L_0
L
0
Regularization
Christos Louizos
Max Welling
Diederik P. Kingma
1.7K
1,280
0
04 Dec 2017
To prune, or not to prune: exploring the efficacy of pruning for model compression
Michael Zhu
Suyog Gupta
510
1,441
0
05 Oct 2017
Extrapolation and learning equations
International Conference on Learning Representations (ICLR), 2016
Georg Martius
Christoph H. Lampert
307
201
0
10 Oct 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han
Huizi Mao
W. Dally
3DGS
1.4K
9,898
0
01 Oct 2015
Deep Learning with Limited Numerical Precision
Suyog Gupta
A. Agrawal
K. Gopalakrishnan
P. Narayanan
HAI
665
2,165
0
09 Feb 2015
Adam: A Method for Stochastic Optimization
International Conference on Learning Representations (ICLR), 2014
Diederik P. Kingma
Jimmy Ba
ODL
5.0K
165,267
0
22 Dec 2014
1
Page 1 of 1
