Vishnu Jejjala

According to our database, Vishnu Jejjala authored at least 21 papers between 2012 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Topological Effects in Neural Network Field Theory.

Christian Ferko, James Halverson, Vishnu Jejjala, Brandon Robinson

CoRR, April, 2026

Machine learning modularity.

Yi Fan, Vishnu Jejjala, Yang Lei

CoRR, January, 2026

2025

Machine learning automorphic forms for black holes.

Vishnu Jejjala, Suresh Nampuri, Dumisani Nxumalo, Pratik Roy, Abinash Swain

CoRR, May, 2025

Colored Jones Polynomials and the Volume Conjecture.

Mark Hughes, Vishnu Jejjala, P. Ramadevi, Pratik Roy, Vivek Kumar Singh

CoRR, February, 2025

2024

Illuminating new and known relations between knot invariants.

Jessica Craven, Mark Hughes, Vishnu Jejjala, Arjun Kar

Mach. Learn. Sci. Technol., 2024

cymyc - Calabi-Yau Metrics, Yukawas, and Curvature.

Per Berglund, Giorgi Butbaia, Tristan Hübsch, Vishnu Jejjala, Challenger Mishra, Damián Mayorga Peña, Justin Tan

CoRR, 2024

Topological data analysis on noisy quantum computers.

Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson, Mark S. Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

MSSM: A Macaulay2 Package for the Vacuum Moduli Space.

Yang-Hui He, Vishnu Jejjala, Brent D. Nelson, Hal Schenck, Michael Eugene Stillman

ACM Commun. Comput. Algebra, June, 2023

Learning to be Simple.

Yang-Hui He, Vishnu Jejjala, Challenger Mishra, Max Sharnoff

CoRR, 2023

2022

Machine Learned Calabi-Yau Metrics and Curvature.

Per Berglund, Giorgi Butbaia, Tristan Hübsch, Vishnu Jejjala, Damián Mayorga Peña, Challenger Mishra, Justin Tan

CoRR, 2022

Towards Quantum Advantage on Noisy Quantum Computers.

Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson, Mark S. Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh

CoRR, 2022

Identifying equivalent Calabi-Yau topologies: A discrete challenge from math and physics for machine learning.

Vishnu Jejjala, Washington Taylor, Andrew Turner

CoRR, 2022

Efficient Quantum Computation of the Fermionic Boundary Operator.

Ismail Yunus Akhalwaya, Yang-Hui He, Lior Horesh, Vishnu Jejjala, William Kirby, Kugendran Naidoo, Shashanka Ubaru

CoRR, 2022

2021

Machine Learning Kreuzer-Skarke Calabi-Yau Threefolds.

Per Berglund, Ben Campbell, Vishnu Jejjala

CoRR, 2021

Learning knot invariants across dimensions.

Jessica Craven, Mark Hughes, Vishnu Jejjala, Arjun Kar

CoRR, 2021

2020

Neural Network Approximations for Calabi-Yau Metrics.

Vishnu Jejjala, Damian Kaloni Mayorga Pena, Challenger Mishra

CoRR, 2020

Disentangling a Deep Learned Volume Formula.

Jessica Craven, Vishnu Jejjala, Arjun Kar

CoRR, 2020

Baryons from Mesons: A Machine Learning Perspective.

Yarin Gal, Vishnu Jejjala, Damian Kaloni Mayorga Pena, Challenger Mishra

CoRR, 2020

2019

Restriction enzymes use a 24 dimensional coding space to recognize 6 base long DNA sequences.

Thomas D. Schneider, Vishnu Jejjala

CoRR, 2019

2018

hep-th.

Yang-Hui He, Vishnu Jejjala, Brent D. Nelson

CoRR, 2018

2012

Modeling Time's Arrow.

Vishnu Jejjala, Michael Kavic, Djordje Minic, Chia-Hsiung Tze

Entropy, 2012