2026
Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation
Zier Mensch, Lars Holdijk, Samuel Duffield, Maxwell Aifer, Patrick J. Coles, Max Welling, Miranda C. N. Cheng
Analytic Bijections for Smooth and Interpretable Normalizing Flows
Mathis Gerdes, Miranda C. N. Cheng
Weight-Space Physics: Interpretable Hypernetworks for Lattice Quantum Field
Theories (JEPAWG)
Tobias Göbel, Julian Ebelt, Zier Mensch, Mathis Gerdes, Miranda C. N. Cheng
AI & Physics
2026
AI4Physics Workshop @ ICML 2026
QMaxCal: Path-Space Regularization for Open Quantum Control via Girsanov's
Theorem
Merijn Moody, Zier Mensch, Miranda C. N. Cheng, Peter G. Bolhuis, Max Welling
AI & Physics
2026
AI4Physics Workshop @ ICML 2026
Topological Effects in Neural Network Field Theory
Christian Ferko, James Halverson, Vishnu Jejjala, Brandon Robinson
2025
Bijx: Bijections and normalizing flows with JAX/NNX
Mathis Gerdes, Miranda C. N. Cheng
Virasoro Symmetry in Neural Network Field Theories
Brandon Robinson
Conformal Defects in Neural Network Field Theories
Pietro Capuozzo, Brandon Robinson, Benjamin Suzzoni
Bootstrapping non-unitary CFTs
Yu-tin Huang, Shao-Cheng Lee, Henry Liao, Justinas Rumbutis
New punctures for six-dimensional compactifications
Fabio Apruzzi, Noppadol Mekareeya, Brandon Robinson, Alessandro Tomasiello
Nonperturbative trivializing flows for lattice gauge theories
Mathis Gerdes, Pim de Haan, Roberto Bondesan, Miranda C. N. Cheng
Localization and wall-crossing of giant graviton expansions in AdS5
Giorgos Eleftheriou, Sameer Murthy, Martí Rosselló
Cone Vertex Algebras, Mock Theta Functions, and Umbral Moonshine Modules
Miranda C. N. Cheng, Gabriele Sgroi
Class numbers, congruent numbers and umbral moonshine
Miranda C. N. Cheng, John F. R. Duncan, Michael H. Mertens
(Selected publications shown. Full list available on
INSPIRE-HEP.)