39 citations · 56 across the 4 of their papers we have counts for
7 papers
SymbolicGPT: A Generative Transformer Model for Symbolic Regression
Mojtaba Valipour, Bowen You, Maysum Panju +1
Symbolic regression is the task of identifying a mathematical expression that best fits a provided dataset of input and output values. Due to the richness of the space of mathemati…
Symbolically Solving Partial Differential Equations using Deep Learning
Maysum Panju, Kourosh Parand, Ali Ghodsi
We describe a neural-based method for generating exact or approximate solutions to differential equations in the form of mathematical expressions. Unlike other neural methods, our…
A Neuro-Symbolic Method for Solving Differential and Functional Equations
Maysum Panju, Ali Ghodsi
When neural networks are used to solve differential equations, they usually produce solutions in the form of black-box functions that are not directly mathematically interpretable.…
Logic Guided Genetic Algorithms
Dhananjay Ashok, Joseph Scott, Sebastian Wetzel +2
We present a novel Auxiliary Truth enhanced Genetic Algorithm (GA) that uses logical or mathematical constraints as a means of data augmentation as well as to compute loss (in conj…
LGML: Logic Guided Machine Learning
Joseph Scott, Maysum Panju, Vijay Ganesh
We introduce Logic Guided Machine Learning (LGML), a novel approach that symbiotically combines machine learning (ML) and logic solvers with the goal of learning mathematical funct…
Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks
Sebastian J. Wetzel, Roger G. Melko, Joseph Scott +2
In this paper, we introduce interpretable Siamese Neural Networks (SNN) for similarity detection to the field of theoretical physics. More precisely, we apply SNNs to events in spe…