Finding Symmetry Breaking Order Parameters with Euclidean Neural Networks. - Tess E. Smidt; Mario Geiger; Benjamin Kurt Miller (CoRR, 2020)

Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties. - Benjamin Kurt Miller; Mario Geiger; Tess E. Smidt; Frank Noé (CoRR, 2020)

Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time. - Benjamin Kurt Miller; Alex Cole; Gilles Louppe; Christoph Weniger (CoRR, 2020)

Truncated Marginal Neural Ratio Estimation. - Benjamin Kurt Miller; Alex Cole; Patrick Forré; Gilles Louppe; Christoph Weniger (NeurIPS, 2021)

Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation. - Alex Cole; Benjamin Kurt Miller; Samuel J. Witte; Maxwell X. Cai; Meiert W. Grootes; Francesco Nattino; Christoph Weniger (CoRR, 2021)

Automatically detecting anomalous exoplanet transits. - Christoph J. Hönes; Benjamin Kurt Miller; Ana M. Heras; Bernard H. Foing (CoRR, 2021)

Generative Coarse-Graining of Molecular Conformations. - Wujie Wang; Minkai Xu; Chen Cai; Benjamin Kurt Miller; Tess E. Smidt; Yusu Wang 001; Jian Tang 005; Rafael Gómez-Bombarelli (ICML, 2022)

Contrastive Neural Ratio Estimation. - Benjamin Kurt Miller; Christoph Weniger; Patrick Forré (NeurIPS, 2022)

swyft: Truncated Marginal Neural Ratio Estimation in Python. - Benjamin Kurt Miller; Alex Cole; Christoph Weniger; Francesco Nattino; Ou Ku; Meiert W. Grootes (J. Open Source Softw., 2022)

Balancing Simulation-based Inference for Conservative Posteriors. - Arnaud Delaunoy; Benjamin Kurt Miller; Patrick Forré; Christoph Weniger; Gilles Louppe (CoRR, 2023)

Simulation-based Inference with the Generalized Kullback-Leibler Divergence. - Benjamin Kurt Miller; Marco Federici; Christoph Weniger; Patrick Forré (CoRR, 2023)

FlowMM: Generating Materials with Riemannian Flow Matching. - Benjamin Kurt Miller; Ricky T. Q. Chen; Anuroop Sriram; Brandon M. Wood (ICML, 2024)

FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions. - Anuroop Sriram; Benjamin Kurt Miller; Ricky T. Q. Chen; Brandon M. Wood (NeurIPS, 2024)

All-atom Diffusion Transformers: Unified generative modelling of molecules and materials. - Chaitanya K. Joshi; Xiang Fu 005; Yi-Lun Liao; Vahe Gharakhanyan; Benjamin Kurt Miller; Anuroop Sriram; Zachary W. Ulissi (CoRR, 2025)

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching. - Aaron J. Havens; Benjamin Kurt Miller; Bing Yan; Carles Domingo-Enrich; Anuroop Sriram; Brandon M. Wood; Daniel Levine; Bin Hu; Brandon Amos; Brian Karrer; Xiang Fu 005; Guan-Horng Liu; et al. (CoRR, 2025)

sbi reloaded: a toolkit for simulation-based inference workflows. - Jan Boelts; Michael Deistler; Manuel Glöckler; Álvaro Tejero-Cantero; Jan-Matthis Lueckmann; Guy Moss 001; Peter Steinbach; Thomas Moreau 001; Fabio Muratore; Julia Linhart; Conor Durkan; Julius Vetter; et al. (J. Open Source Softw., 2025)

Adjoint Schrödinger Bridge Sampler. - Guan-Horng Liu; Jaemoo Choi; Yongxin Chen; Benjamin Kurt Miller; Ricky T. Q. Chen (CoRR, 2025)