2026
Common task framework for a critical evaluation of scientific machine learning algorithms
P. Wyder and J. Goldfeder and A. Yermakov and Y. Zhao and S. Riva and J. Williams and D. Zoro and A. Rude and M. Tomasetto and J. Germany and J. Bakarji and G. Maierhofer and M. Cranmer and N. Kutz
Advances in Neural Information Processing Systems
The seismic wavefield common task framework
A. Yermakov and Y. Zhao and M. Denolle and Y. Ni and P. Wyder and J. Goldfeder and S. Riva and J. Williams and D. Zoro and A. Rude and M. Tomasetto and J. Germany and J. Bakarji and G. Maierhofer and M. Cranmer and N. Kutz
International Conference on Learning Representations
CTF4Nuclear: Common Task Framework for Nuclear Fission and Fusion Models
S. Riva and C. Introini and A. Cammi and D. Price and A. Yermakov and Y. Zhao and P. M. Wyder and J. Goldfeder and J. Williams and A. S. Rude and M. Tomasetto and J. Germany and J. Bakarji and G. Maierhofer and M. Cranmer and J. N. Kutz
arXiv preprint arXiv:2605.15549
The Circle of Fifths as Latent Geometry in Bach's Well-Tempered Clavier
N. Sadek and J. Bakarji
1st International Workshop on Emerging AI Technologies for Music
EML Trees Are Universal Approximators
J. Germany and E. Abdo and J. Bakarji
arXiv preprint arXiv:2606.23179
Discovery of Symbolic Hamiltonian Expressions with Buckingham-Symplectic Networks
J. Germany and J. Bakarji and S. Najem
arXiv preprint arXiv:2604.00576
2025
Statistical mechanics of dynamical system identification
A. A. Klishin and J. Bakarji and J. N. Kutz and K. Manohar
Physical Review Research
Discovering Multi-Scale Semantic Structure in Text Corpora Using Density-Based Trees and LLM Embeddings
T. Haschka and J. Bakarji
arXiv preprint arXiv:2512.23471
Semantic Tree Inference on Text Corpa using a Nested Density Approach together with Large Language Model Embeddings
T. Haschka and J. Bakarji
arXiv preprint arXiv:2512.23471
2024
Role of physics in physics-informed machine learning
A. Chandra and J. Bakarji and D. M. Tartakovsky
Journal of Machine Learning for Modeling and Computing
Distilling data into code: Algorithm discovery
J. Bakarji
Nature Computational Science
2023
Discovering governing equations from partial measurements with deep delay autoencoders
J. Bakarji and K. Champion and J. N. Kutz and S. L. Brunton
Proceedings of the Royal Society A, 2023
2022
Dimensionally consistent learning with Buckingham Pi
J. Bakarji and J. Callaham and S. L. Brunton and J. N. Kutz
Nature Computational Science
2021
Data-driven discovery of coarse-grained equations
J. Bakarji and D. M. Tartakovsky
Journal of Computational Physics
Unsupervised Learning of Dimensionless Groups and Minimally Parametrized Equations
J. Bakarji and S. Brunton and N. Kutz and J. Callaham
APS Division of Fluid Dynamics Meeting Abstracts
2020
Stochastic pore collapse models in granular materials
J. Bakarji and D. M. Tartakovsky
arXiv preprint arXiv:2002.12479
Stochastic Multiscale Modeling of Complex Materials
J. Bakarji
Machine Learning for a Music Glove Instrument
J. Bakarji
arXiv preprint arXiv:2001.09551
2019
Microstructural heterogeneity drives reaction initiation in granular materials
J. Bakarji and D. M. Tartakovsky
Applied physics letters
2017
Agent-based socio-hydrological hybrid modeling for water resource management
J. Bakarji and D. O’Malley and V. V. Vesselinov
Water Resources Management
On the use of reverse Brownian motion to accelerate hybrid simulations
J. Bakarji and D. M. Tartakovsky
Journal of Computational Physics
When was it written?
J. Bakarji and D. Belivanis and S. Nezami
Journal Of Machine Learning
2014
Multiscale Simulations of Reactive Transport
D. M. Tartakovsky and J. Bakarji
AGU Fall Meeting Abstracts
2013
A reduced-order model of a microfluidic transistor
J. Bakarji and K. Keniar and M. Cheikh and I. Lakkis
ASME International Mechanical Engineering Congress and Exposition
Unknown
Symbolic Hamiltonian Discovery with Buckingham-Symplectic Networks
J. Germany and S. Najem and J. Bakarji
Available at SSRN 7048502
When Bigger isn't Better: The Role of Model-Data Complexity in Time Series Forecasts
N. Y. Lo and J. Bakarji and Y. Zhao and J. N. Kutz