Papers

Selected publications, newest first. A complete, always-current list is on Google Scholar and NASA/ADS.

DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking. M. L. Wiemann, L. M. Smith, P. Melchior, S. Mishra-Sharma, A. G. Wilson, et al. (incl. C. Cuesta-Lazaro) arXiv preprint.

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Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics. P. Mercader-Perez, C. Cuesta-Lazaro, D. Muthukrishna, J. Audenaert, et al. arXiv preprint.

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Augmenting Representations with Scientific Papers. N. O. P. Vago, R. Di Tella, C. Cuesta-Lazaro, M. J. Smith, C. Garraffo, et al. arXiv preprint.

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How DREAMS Are Made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds. T. Nguyen, F. Villaescusa-Navarro, S. Mishra-Sharma, C. Cuesta-Lazaro, et al. The Astrophysical Journal 997 (2).

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BaryonBridge: A Stochastic Interpolant Model for Fast Hydrodynamical Simulations. B. Horowitz, C. Cuesta-Lazaro, O. Yehia. arXiv preprint.

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Hierarchical Simulation-Based Inference of Supernova Power Sources and their Physical Properties. E. P. Vidal, A. T. Gagliano, C. Cuesta-Lazaro. arXiv preprint.

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High-Redshift Millennium and Astrid Galaxies in Effective Field Theory at the Field Level. J. M. Sullivan, C. Cuesta-Lazaro, M. M. Ivanov, Y. Ni, S. Bose, B. Hadzhiyska, et al. Physical Review D 112 (8).

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Cosmoflow: Scale-Aware Representation Learning for Cosmology with Flow Matching. S. Kannan, T. Qiu, C. Cuesta-Lazaro, H. Jeong. arXiv preprint.

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Detecting Model Misspecification in Cosmology with Scale-Dependent Normalizing Flows. A. Akhmetzhanova, C. Cuesta-Lazaro, S. Mishra-Sharma. Machine Learning: Science and Technology 6 (4).

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A Parameter-Masked Mock Data Challenge for Beyond-Two-Point Galaxy Clustering Statistics. Beyond-2pt Collaboration (incl. C. Cuesta-Lazaro). The Astrophysical Journal 990 (2).

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Unsupervised Searches for Cosmological Parity Violation: Improving Detection Power with the Neural Field Scattering Transform. M. Craigie, P. L. Taylor, Y. S. Ting, C. Cuesta-Lazaro, R. Ruggeri, T. M. Davis. Physical Review D 112 (2).

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Cosmological Constraints from the Minkowski Functionals of the BOSS CMASS Galaxy Sample. W. Liu, E. Paillas, C. Cuesta-Lazaro, G. Valogiannis, W. Fang. Journal of Cosmology and Astroparticle Physics 2025 (05).

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A Theoretical Approach to Density-Split Clustering. M. Pinon, A. De Mattia, Ö. Burtin, V. Ruhlmann-Kleider, S. Codis, E. Paillas, et al. (incl. C. Cuesta-Lazaro) Journal of Cosmology and Astroparticle Physics 2025 (05).

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Full-Shape Analysis with Simulation-Based Priors: Cosmological Parameters and the Structure Growth Anomaly. M. M. Ivanov, A. Obuljen, C. Cuesta-Lazaro, M. W. Toomey. Physical Review D 111 (6).

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Emulation of f(R) Modified Gravity from ΛCDM using Conditional GANs. Y. Gondhalekar, S. Bose, B. Li, C. Cuesta-Lazaro. Monthly Notices of the Royal Astronomical Society 536 (2).

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An LLM-Driven Framework for Cosmological Model-Building and Exploration. N. Mudur, C. Cuesta-Lazaro, M. W. Toomey, D. Finkbeiner. LLM for Scientific Discovery Workshop.

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Diffusion-HMC: Parameter Inference with Diffusion-Model-Driven Hamiltonian Monte Carlo. N. Mudur, C. Cuesta-Lazaro, D. P. Finkbeiner. The Astrophysical Journal 978 (1).

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The Millennium and Astrid Galaxies in Effective Field Theory: Comparison with Galaxy–Halo Connection Models at the Field Level. M. M. Ivanov, C. Cuesta-Lazaro, A. Obuljen, M. W. Toomey, Y. Ni, S. Bose, et al. arXiv preprint.

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Joint Cosmological Parameter Inference and Initial Condition Reconstruction with Stochastic Interpolants. C. Cuesta-Lazaro, A. Bayer, M. Albergo, S. Mishra-Sharma, C. Modi, et al. NeurIPS Workshop on Machine Learning and the Physical Sciences.

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A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing. J. Balla, S. Mishra-Sharma, C. Cuesta-Lazaro, T. Jaakkola, T. Smidt. arXiv preprint.

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Full-Shape Analysis with Simulation-Based Priors: Constraints on Single-Field Inflation from BOSS. M. M. Ivanov, C. Cuesta-Lazaro, S. Mishra-Sharma, A. Obuljen, M. W. Toomey. Physical Review D 110 (6).

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Debiasing with Diffusion: Probabilistic Reconstruction of Dark Matter Fields from Galaxies with CAMELS. V. Ono, C. F. Park, N. Mudur, Y. Ni, C. Cuesta-Lazaro, F. Villaescusa-Navarro. The Astrophysical Journal 970 (2).

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SUNBIRD: A Simulation-Based Model for Full-Shape Density-Split Clustering. C. Cuesta-Lazaro, E. Paillas, S. Yuan, Y.-C. Cai, S. Nadathur, W. J. Percival, et al. Monthly Notices of the Royal Astronomical Society 531 (3).

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Point Cloud Approach to Generative Modeling for Galaxy Surveys at the Field Level. C. Cuesta-Lazaro, S. Mishra-Sharma. Physical Review D 109 (12).

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Cosmological Constraints from Density-Split Clustering in the BOSS CMASS Galaxy Sample. E. Paillas, C. Cuesta-Lazaro, W. J. Percival, S. Nadathur, Y.-C. Cai, S. Yuan, et al. Monthly Notices of the Royal Astronomical Society 531 (1).

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LtU-ILI: An All-In-One Framework for Implicit Inference in Astrophysics and Cosmology. M. Ho, D. J. Bartlett, N. Chartier, C. Cuesta-Lazaro, et al. arXiv preprint.

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3D Reconstruction of Dark Matter Fields with Diffusion Models: Towards Application to Galaxy Surveys. C. F. Park, N. Mudur, C. Cuesta-Lazaro, Y. Ni, V. Ono, D. Finkbeiner. ICML 2024 AI for Science Workshop.

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An Emulator-Based Halo Model in Modified Gravity — I. The Halo Concentration–Mass Relation and Density Profile. C.-Z. Ruan, C. Cuesta-Lazaro, A. Eggemeier, B. Li, C. M. Baugh, C. Arnold, et al. Monthly Notices of the Royal Astronomical Society 527 (2).

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Cosmological Field Emulation and Parameter Inference with Diffusion Models. N. Mudur, C. Cuesta-Lazaro, D. P. Finkbeiner. arXiv preprint.

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Learning an Effective Evolution Equation for Particle-Mesh Simulations Across Cosmologies. N. Payot, P. Lemos, L. Perreault-Levasseur, C. Cuesta-Lazaro, C. Modi, et al. arXiv preprint.

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Probabilistic Reconstruction of Dark Matter Fields from Biased Tracers using Diffusion Models. C. F. Park, V. Ono, N. Mudur, Y. Ni, C. Cuesta-Lazaro. arXiv preprint.

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MGLenS: Modified Gravity Weak Lensing Simulations for Emulation-Based Cosmological Inference. J. Harnois-Déraps, C. Hernandez-Aguayo, C. Cuesta-Lazaro, C. Arnold, et al. Monthly Notices of the Royal Astronomical Society 525 (4).

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Simulation-Based Inference for Exoplanet Atmospheric Retrieval: Insights from Winning the Ariel Data Challenge 2023 using Normalizing Flows. M. Aubin, C. Cuesta-Lazaro, E. Tregidga, J. Viaña, C. Garraffo, I. E. Gordon, et al. ECML PKDD 2023.

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Galaxy Clustering from the Bottom Up: A Streaming Model Emulator I. C. Cuesta-Lazaro, T. Nishimichi, Y. Kobayashi, C.-Z. Ruan, A. Eggemeier, et al. Monthly Notices of the Royal Astronomical Society 523 (3).

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Constraining νΛCDM with Density-Split Clustering. E. Paillas, C. Cuesta-Lazaro, P. Zarrouk, Y.-C. Cai, W. J. Percival, S. Nadathur, et al. Monthly Notices of the Royal Astronomical Society 522 (1).

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Don't Simulate Twice: One-Shot Sensitivity Analyses via Automatic Differentiation. A. Quera-Bofarull, A. Chopra, J. Aylett-Bullock, C. Cuesta-Lazaro, et al. AAMAS 2023.

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Bayesian Emulation and History Matching of JUNE. I. Vernon, J. Owen, J. Aylett-Bullock, C. Cuesta-Lazaro, J. Frawley, et al. Philosophical Transactions of the Royal Society A 380 (2).

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Towards an Accurate Model of Small-Scale Redshift-Space Distortions in Modified Gravity. C.-Z. Ruan, C. Cuesta-Lazaro, A. Eggemeier, C. Hernández-Aguayo, et al. Monthly Notices of the Royal Astronomical Society 514 (1).

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What Does the Sea Say to the Shore? A BERT-Based DST-Style Approach for Speaker-to-Dialogue Attribution in Novels. C. Cuesta-Lazaro, A. Prasad, T. Wood. Proceedings of the 60th Annual Meeting of the ACL.

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Epidemiological Modelling in Refugee and Internally Displaced People Settlements: Challenges and Ways Forward. J. Aylett-Bullock, R. T. Gilman, I. Hall, D. Kennedy, E. S. Evers, A. Katta, et al. (incl. C. Cuesta-Lazaro) BMJ Global Health 7 (3).

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Towards Testing the Theory of Gravity with DESI: Summary Statistics, Model Predictions and Future Simulation Requirements. S. Alam, C. Arnold, A. Aviles, R. Bean, Y.-C. Cai, M. Cautun, et al. (incl. C. Cuesta-Lazaro) Journal of Cosmology and Astroparticle Physics 2021 (11).

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Vaccinations or Non-Pharmaceutical Interventions: Safe Reopening of Schools in England. C. Cuesta-Lazaro, A. Quera-Bofarull, J. Aylett-Bullock, B. N. Lawrence, et al. medRxiv preprint.

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JUNE: Open-Source Individual-Based Epidemiology Simulation. J. Aylett-Bullock, C. Cuesta-Lazaro, A. Quera-Bofarull, M. Icaza-Lizaola, et al. Royal Society Open Science 8 (7).

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Towards a Non-Gaussian Model of Redshift-Space Distortions. C. Cuesta-Lazaro, B. Li, A. Eggemeier, P. Zarrouk, C. M. Baugh, T. Nishimichi, et al. Monthly Notices of the Royal Astronomical Society 498 (1).

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XNet: A Convolutional Neural Network (CNN) Implementation for Medical X-Ray Image Segmentation Suitable for Small Datasets. J. Bullock, C. Cuesta-Lázaro, A. Quera-Bofarull. SPIE Medical Imaging 2019.

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