ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2004.11170
  4. Cited By
Learning a Formula of Interpretability to Learn Interpretable Formulas

Learning a Formula of Interpretability to Learn Interpretable Formulas

23 April 2020
M. Virgolin
A. D. Lorenzo
Eric Medvet
Francesca Randone
ArXivPDFHTML

Papers citing "Learning a Formula of Interpretability to Learn Interpretable Formulas"

11 / 11 papers shown
Title
Social Interpretable Reinforcement Learning
Social Interpretable Reinforcement Learning
Leonardo Lucio Custode
Giovanni Iacca
OffRL
42
2
0
27 Jan 2024
Differentiable Genetic Programming for High-dimensional Symbolic
  Regression
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
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
Pierre-Alexandre Kamienny
Guillaume Lample
Sylvain Lamprier
M. Virgolin
34
25
0
22 Feb 2023
Less is More: A Call to Focus on Simpler Models in Genetic Programming
  for Interpretable Machine Learning
Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning
M. Virgolin
Eric Medvet
Tanja Alderliesten
Peter A. N. Bosman
26
6
0
05 Apr 2022
Evolvability Degeneration in Multi-Objective Genetic Programming for
  Symbolic Regression
Evolvability Degeneration in Multi-Objective Genetic Programming for Symbolic Regression
Dazhuang Liu
M. Virgolin
Tanja Alderliesten
Peter A. N. Bosman
44
12
0
14 Feb 2022
Interpretable pipelines with evolutionarily optimized modules for RL
  tasks with visual inputs
Interpretable pipelines with evolutionarily optimized modules for RL tasks with visual inputs
Leonardo Lucio Custode
Giovanni Iacca
27
13
0
10 Feb 2022
Contemporary Symbolic Regression Methods and their Relative Performance
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
47
249
0
29 Jul 2021
Model Learning with Personalized Interpretability Estimation (ML-PIE)
Model Learning with Personalized Interpretability Estimation (ML-PIE)
M. Virgolin
A. D. Lorenzo
Francesca Randone
Eric Medvet
M. Wahde
24
29
0
13 Apr 2021
Evolutionary learning of interpretable decision trees
Evolutionary learning of interpretable decision trees
Leonardo Lucio Custode
Giovanni Iacca
OffRL
41
40
0
14 Dec 2020
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
257
3,690
0
28 Feb 2017
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,090
0
24 Oct 2016
1