Publications

Publications and preprints are listed chronologically. A Google Scholar BibTeX export can be placed at /publications/publications.bib and linked here as a machine-readable bibliography.

BibTeX

Preprints

• 2026. A. Bao, J. Lai, W. Gilpin. Transformers for dynamical systems learn transfer operators in-context. arXiv.
• 2026. M. S. Krieger, W. Gilpin. Discovering causal nonlinear networks from single-cell gene expression. Preprint.

2026

• A. Bao, H. Vattikuti, J. Lai, W. Gilpin. Universal redundancies in time series foundation models. International Conference on Machine Learning (ICML).
• J. Lai, A. Bao, W. Gilpin. Panda: A pretrained forecast model for chaotic dynamics. International Conference on Learning Representations (ICLR).
• Y. Zhang, W. Gilpin. Context parroting: A simple but tough-to-beat baseline for foundation models in scientific machine learning. International Conference on Learning Representations (ICLR).
• M. Bauer et al. Unifying theories in high-dimensional biophysics: approaches, challenges and opportunities. npj Systems Biology and Applications.

2025

• W. Gilpin. Recurrences reveal shared causal drivers of complex time series. Physical Review X.
• Y. Zhang, W. Gilpin. Zero-shot forecasting of chaotic systems. International Conference on Learning Representations (ICLR).
• W. Gilpin. Optimization hardness constrains ecological transients. PLOS Computational Biology.
• W. Gilpin. The cell as a token: high-dimensional geometry in language models and cell embeddings. Bioinformatics.
• J. Yik et al. The NeuroBench framework for benchmarking neuromorphic computing algorithms and systems. Nature Communications.

2024

• W. Gilpin. Generative learning for nonlinear dynamics. Nature Reviews Physics.
• M. J. Falk, F. Roach, W. Gilpin, A. Murugan. Curiosity-driven search for novel non-equilibrium behaviors. Physical Review Research.

2023

• W. Gilpin. Model scale versus domain knowledge in statistical forecasting of chaotic systems. Physical Review Research.

2021

• W. Gilpin. Chaos as an interpretable benchmark for forecasting and data-driven modelling. Neural Information Processing Systems (NeurIPS).
• W. Gilpin. Desynchronization of jammed oscillators by avalanches. Physical Review Research.

2020

• W. Gilpin. Deep reconstruction of strange attractors from time series. Neural Information Processing Systems (NeurIPS).
• W. Gilpin, Y. Huang, D. Forger. Learning dynamics from large biological data sets: Machine learning meets systems biology. Current Opinion in Systems Biology.
• W. Gilpin, M. S. Bull, M. Prakash. The multiscale physics of cilia and flagella. Nature Reviews Physics.

2019

• W. Gilpin. Cellular automata as convolutional neural networks. Physical Review E.

2018

• W. Gilpin. Cryptographic hashing using chaotic hydrodynamics. Proceedings of the National Academy of Sciences.
• W. Gilpin, M. W. Feldman. Cryptic selection forces and dynamic heritability in generalized phenotypic evolution. Theoretical Population Biology.
• J. Y. Wakano, W. Gilpin, S. Kadowaki, M. W. Feldman, K. Aoki. Ecocultural range-expansion scenarios for the replacement or assimilation of Neanderthals by modern humans. Theoretical Population Biology.
• W. Gilpin, V. N. Prakash, M. Prakash. Rapid behavioral transitions produce chaotic mixing by a planktonic microswimmer. arXiv.

2017

• W. Gilpin, M. W. Feldman. A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape. PLOS Computational Biology.
• W. Gilpin, V. N. Prakash, M. Prakash. Flowtrace: simple visualization of coherent structures in biological fluid flows. Journal of Experimental Biology.
• W. Gilpin, V. N. Prakash, M. Prakash. Vortex arrays and ciliary tangles underlie the feeding-swimming trade-off in starfish larvae. Nature Physics.
• W. Gilpin, V. N. Prakash, M. Prakash. Dynamic vortex arrays created by starfish larvae. Physical Review Fluids.
• W. Gilpin, V. N. Prakash, M. Prakash. Reply to “Boundary effects on currents around ciliated larvae”. Nature Physics.

2016

• W. Gilpin, M. W. Feldman, K. Aoki. An ecocultural model predicts Neanderthal extinction through competition with modern humans. Proceedings of the National Academy of Sciences.

2015

• W. Gilpin. PyPDB: A Python API for the Protein Data Bank. Bioinformatics.
• W. Gilpin, S. Uppaluri, C. P. Brangwynne. Worms under pressure: bulk mechanical properties of C. elegans are independent of the cuticle. Biophysical Journal.

2014

• K. Bayat, W. K. C. Sun, W. Gilpin, M. Baroughi, M. Lončar. Formation of nitrogen-vacancy center ensembles in diamond nanowires. CLEO: Science and Innovations.

Bibliographic ordering and years follow the August 2026 CV. Last updated August 2026.