A neural simulation-based inference approach for characterizing the Galactic Center γ-ray excess. - Siddharth Mishra-Sharma; Kyle Cranmer (CoRR, 2021)

Machine Learning and Cosmology. - Cora Dvorkin; Siddharth Mishra-Sharma; Brian Nord; V. Ashley Villar; Camille Avestruz; Keith Bechtol; Aleksandra Ciprijanovic; Andrew J. Connolly; Lehman H. Garrison; Gautham Narayan; Francisco Villaescusa-Navarro (CoRR, 2022)

Strong Lensing Source Reconstruction Using Continuous Neural Fields. - Siddharth Mishra-Sharma; Ge Yang (CoRR, 2022)

Uncovering dark matter density profiles in dwarf galaxies with graph neural networks. - Tri Nguyen; Siddharth Mishra-Sharma; Reuel Williams; Lina Necib (CoRR, 2022)

Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimation. - Gemma Zhang; Siddharth Mishra-Sharma; Cora Dvorkin (CoRR, 2022)

Inferring dark matter substructure with astrometric lensing beyond the power spectrum. - Siddharth Mishra-Sharma (Mach. Learn. Sci. Technol., 2022)

Data Compression and Inference in Cosmology with Self-Supervised Machine Learning. - Aizhan Akhmetzhanova; Siddharth Mishra-Sharma; Cora Dvorkin (CoRR, 2023)

A point cloud approach to generative modeling for galaxy surveys at the field level. - Carolina Cuesta-Lázaro; Siddharth Mishra-Sharma (CoRR, 2023)

PAPERCLIP: Associating Astronomical Observations and Natural Language with Multi-Modal Models. - Siddharth Mishra-Sharma; Yiding Song; Jesse Thaler (CoRR, 2024)

Low-Budget Simulation-Based Inference with Bayesian Neural Networks. - Arnaud Delaunoy; Maxence de la Brassinne Bonardeaux; Siddharth Mishra-Sharma; Gilles Louppe (CoRR, 2024)

Maven: A Multimodal Foundation Model for Supernova Science. - Gemma Zhang; Thomas Helfer; Alexander T. Gagliano; Siddharth Mishra-Sharma; V. Ashley Villar (CoRR, 2024)

How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds. - Tri Nguyen; Francisco Villaescusa-Navarro; Siddharth Mishra-Sharma; Carolina Cuesta-Lázaro; Paul Torrey; Arya Farahi; Alex M. Garcia; Jonah C. Rose; Stephanie O'Neil; Mark Vogelsberger; Xuejian Shen; Cian Roche; et al. (CoRR, 2024)

A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing. - Julia Balla; Siddharth Mishra-Sharma; Carolina Cuesta-Lázaro; Tommi S. Jaakkola; Tess E. Smidt (CoRR, 2024)

Hierarchical Neural Simulation-Based Inference Over Event Ensembles. - Lukas Heinrich; Siddharth Mishra-Sharma; Chris Pollard; Philipp Windischhofer (Trans. Mach. Learn. Res., 2024)

A generative modeling approach to reconstructing 21 cm tomographic data. - Nashwan Sabti; Ram Purandhar Reddy Sudha; Julian B. Muñoz; Siddharth Mishra-Sharma; Taewook Youn (Mach. Learn. Sci. Technol., 2025)

Auditing language models for hidden objectives. - Samuel Marks; Johannes Treutlein; Trenton Bricken; Jack Lindsey; Jonathan Marcus; Siddharth Mishra-Sharma; Daniel M. Ziegler; Emmanuel Ameisen; Joshua Batson; Tim Belonax; Samuel R. Bowman; Shan Carter; et al. (CoRR, 2025)