Research papers
Papers about BrainX.
Core publications describing the BrainX framework and its scientific foundations — spanning differentiable brain simulation, just-in-time compilation for neural dynamics, physical-unit-aware AI computing, and online learning in spiking networks. Together these works define the methods and design principles behind the BrainX ecosystem.
Integrating physical units into high-performance AI-driven scientific computing
BrainUnit Read paper →BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming
BrainPy Read paper →A differentiable brain simulator bridging brain simulation and brain-inspired computing
BrainPy Read paper →A Differentiable Approach to Multi-scale Brain Modeling
Differentiable Simulation Read paper →A just-in-time compilation approach for neural dynamics simulation
BrainPy Read paper →Citing BrainX.
If your work uses or builds on BrainX, please cite the canonical papers
below. For finer attribution to a specific ecosystem package
(brainstate, braincell, brainmass, …), see that package's
CITATION.cff on GitHub.
- eLife · 2023 · Framework paper
Wang, C., et al. (2023). BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming. eLife, 12, e86365. https://doi.org/10.7554/eLife.86365
@article{wang2023brainpy, author = {Wang, Chaoming and others}, title = {{BrainPy}, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming}, journal = {eLife}, volume = {12}, pages = {e86365}, year = {2023}, doi = {10.7554/eLife.86365} } - ICLR · 2024 · Differentiable simulation
Wang, C., et al. (2024). A differentiable brain simulator bridging brain simulation and brain-inspired computing. In International Conference on Learning Representations. openreview.net/forum?id=AU2gS9ut61
@inproceedings{wang2024differentiable, author = {Wang, Chaoming and others}, title = {A differentiable brain simulator bridging brain simulation and brain-inspired computing}, booktitle = {International Conference on Learning Representations (ICLR)}, year = {2024}, url = {https://openreview.net/forum?id=AU2gS9ut61} } - Nature Comm · 2025 · BrainUnit
Wang, C., et al. (2025). Integrating physical units into high-performance AI-driven scientific computing. Nature Communications. https://doi.org/10.1038/s41467-025-58626-4
@article{wang2025brainunit, author = {Wang, Chaoming and others}, title = {Integrating physical units into high-performance {AI}-driven scientific computing}, journal = {Nature Communications}, year = {2025}, doi = {10.1038/s41467-025-58626-4} } - Nature Comm · 2026 · BrainTrace
Wang, C., et al. (2026). Model-agnostic linear-memory online learning in spiking neural networks. Nature Communications. https://doi.org/10.1038/s41467-026-68453-w
@article{wang2026braintrace, author = {Wang, Chaoming and others}, title = {Model-agnostic linear-memory online learning in spiking neural networks}, journal = {Nature Communications}, year = {2026}, doi = {10.1038/s41467-026-68453-w} }