Orbanz, Peter

13 publications

ICLR 2025 Designing Mechanical Meta-Materials by Learning Equivariant Flows Mehran Mirramezani, Anne S. Meeussen, Katia Bertoldi, Peter Orbanz, Ryan P Adams

ICML 2025 Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrödinger Equation Kevin Han Huang, Ni Zhan, Elif Ertekin, Peter Orbanz, Ryan P Adams

ICML 2025 Distinguishing Cause from Effect with Causal Velocity Models Johnny Xi, Hugh Dance, Peter Orbanz, Benjamin Bloem-Reddy

ICML 2025 Efficiently Vectorized MCMC on Modern Accelerators Hugh Dance, Pierre Glaser, Peter Orbanz, Ryan P Adams

NeurIPS 2023 The Graph Pencil Method: Mapping Subgraph Densities to Stochastic Block Models Lee Gunderson, Gecia Bravo-Hermsdorff, Peter Orbanz

ICMLW 2023 The Pairwise Prony Algorithm: Efficient Inference of Stochastic Block Models with Prescribed Subgraph Densities Lee M. Gunderson, Gecia Bravo-Hermsdorff, Peter Orbanz

AISTATS 2019 Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data Victor Veitch, Morgane Austern, Wenda Zhou, David M. Blei, Peter Orbanz

ICLR 2019 Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach Wenda Zhou, Victor Veitch, Morgane Austern, Ryan P. Adams, Peter Orbanz

NeurIPS 2012 Random Function Priors for Exchangeable Arrays with Applications to Graphs and Relational Data James Lloyd, Peter Orbanz, Zoubin Ghahramani, Daniel M. Roy

AISTATS 2010 Dependent Indian Buffet Processes Sinead Williamson, Peter Orbanz, Zoubin Ghahramani

NeurIPS 2009 Construction of Nonparametric Bayesian Models from Parametric Bayes Equations Peter Orbanz

ICML 2007 Cluster Analysis of Heterogeneous Rank Data Ludwig M. Busse, Peter Orbanz, Joachim M. Buhmann

ECCV 2006 Smooth Image Segmentation by Nonparametric Bayesian Inference Peter Orbanz, Joachim M. Buhmann