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. 2401.11513
  4. Cited By
Exploring the Truth and Beauty of Theory Landscapes with Machine
  Learning

Exploring the Truth and Beauty of Theory Landscapes with Machine Learning

21 January 2024
Konstantin T. Matchev
Katia Matcheva
Pierre Ramond
Sarunas Verner
ArXivPDFHTML

Papers citing "Exploring the Truth and Beauty of Theory Landscapes with Machine Learning"

5 / 5 papers shown
Title
Truth, beauty, and goodness in grand unification: a machine learning
  approach
Truth, beauty, and goodness in grand unification: a machine learning approach
Shinsuke Kawai
Nobuchika Okada
21
1
0
11 Nov 2024
Seeking Truth and Beauty in Flavor Physics with Machine Learning
Seeking Truth and Beauty in Flavor Physics with Machine Learning
Konstantin T. Matchev
Katia Matcheva
Pierre Ramond
Sarunas Verner
AI4CE
11
2
0
31 Oct 2023
Exploring the flavor structure of quarks and leptons with reinforcement
  learning
Exploring the flavor structure of quarks and leptons with reinforcement learning
Satsuki Nishimura
Coh Miyao
Hajime Otsuka
8
8
0
27 Apr 2023
Learning Symbolic Physics with Graph Networks
Learning Symbolic Physics with Graph Networks
M. Cranmer
Rui Xu
Peter W. Battaglia
S. Ho
PINN
AI4CE
175
83
0
12 Sep 2019
A Compositional Object-Based Approach to Learning Physical Dynamics
A Compositional Object-Based Approach to Learning Physical Dynamics
Michael Chang
T. Ullman
Antonio Torralba
J. Tenenbaum
AI4CE
OCL
226
438
0
01 Dec 2016
1