Benjamin Kurt Miller

32 papers A* 7Journal 25

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Generalizing Coverage Plots for Simulation-based Inference. Trans. Mach. Learn. Res. Maximilian Lipp, Benjamin Kurt Miller, Lyubov Amitonova, Patrick Forré
2026	J	`jnl`	Offline Materials Optimization with CliqueFlowmer. CoRR Jakub Grudzien Kuba, Benjamin Kurt Miller, Sergey Levine, Pieter Abbeel
2025	A*	`conf`	Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching. ICML Aaron J. Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M. Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen
2025	J	`jnl`	Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching. CoRR 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, Guan-Horng Liu, Ricky T. Q. Chen
2025	J	`jnl`	Adjoint Schrödinger Bridge Sampler. CoRR Guan-Horng Liu, Jaemoo Choi, Yongxin Chen, Benjamin Kurt Miller, Ricky T. Q. Chen
2025	A*	`conf`	All-atom Diffusion Transformers: Unified generative modelling of molecules and materials. ICML Chaitanya K. Joshi, Xiang Fu, Yi-Lun Liao, Vahe Gharakhanyan, Benjamin Kurt Miller, Anuroop Sriram, Zachary W. Ulissi
2025	J	`jnl`	All-atom Diffusion Transformers: Unified generative modelling of molecules and materials. CoRR Chaitanya K. Joshi, Xiang Fu, Yi-Lun Liao, Vahe Gharakhanyan, Benjamin Kurt Miller, Anuroop Sriram, Zachary W. Ulissi
2025	J	`jnl`	Enhancing Diffusion-Based Sampling with Molecular Collective Variables. CoRR Juno Nam, Bálint Máté, Artur P. Toshev, Manasa Kaniselvan, Rafael Gómez-Bombarelli, Ricky T. Q. Chen, Brandon M. Wood, Guan-Horng Liu, Benjamin Kurt Miller
2025	J	`jnl`	Learning from the electronic structure of molecules across the periodic table. CoRR Manasa Kaniselvan, Benjamin Kurt Miller, Meng Gao, Juno Nam, Daniel S. Levine
2025	J	`jnl`	Simulation-Based Inference: A Practical Guide. CoRR Michael Deistler, Jan Boelts, Peter Steinbach, Guy Moss, Thomas Moreau, Manuel Glöckler, Pedro L. C. Rodrigues, Julia Linhart, Janne K. Lappalainen, Benjamin Kurt Miller, Pedro J. Gonçalves, Jan-Matthis Lueckmann, Cornelius Schröder, Jakob H. Macke
2025	J	`jnl`	Space Group Conditional Flow Matching. CoRR Omri Puny, Yaron Lipman, Benjamin Kurt Miller
2025	J	`jnl`	The Loss Landscape of Powder X-Ray Diffraction-Based Structure Optimization Is Too Rough for Gradient Descent. CoRR Nofit Segal, Akshay Subramanian, Mingda Li, Benjamin Kurt Miller, Rafael Gómez-Bombarelli
2025	J	`jnl`	sbi reloaded: a toolkit for simulation-based inference workflows. J. Open Source Softw. Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke
2024	A*	`conf`	FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions. NeurIPS Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood
2024	J	`jnl`	FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions. CoRR Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood
2024	A*	`conf`	FlowMM: Generating Materials with Riemannian Flow Matching. ICML Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram, Brandon M. Wood
2024	J	`jnl`	FlowMM: Generating Materials with Riemannian Flow Matching. CoRR Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram, Brandon M. Wood
2024	J	`jnl`	sbi reloaded: a toolkit for simulation-based inference workflows. CoRR Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke
2023	J	`jnl`	Balancing Simulation-based Inference for Conservative Posteriors. CoRR Arnaud Delaunoy, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger, Gilles Louppe
2023	J	`jnl`	Simulation-based Inference with the Generalized Kullback-Leibler Divergence. CoRR Benjamin Kurt Miller, Marco Federici, Christoph Weniger, Patrick Forré
2022	A*	`conf`	Contrastive Neural Ratio Estimation. NeurIPS Benjamin Kurt Miller, Christoph Weniger, Patrick Forré
2022	J	`jnl`	Contrastive Neural Ratio Estimation. CoRR Benjamin Kurt Miller, Christoph Weniger, Patrick Forré
2022	A*	`conf`	Generative Coarse-Graining of Molecular Conformations. ICML Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess E. Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli
2022	J	`jnl`	Generative Coarse-Graining of Molecular Conformations. CoRR Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess E. Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli
2022	J	`jnl`	swyft: Truncated Marginal Neural Ratio Estimation in Python. J. Open Source Softw. Benjamin Kurt Miller, Alex Cole, Christoph Weniger, Francesco Nattino, Ou Ku, Meiert W. Grootes
2021	J	`jnl`	Automatically detecting anomalous exoplanet transits. CoRR Christoph J. Hönes, Benjamin Kurt Miller, Ana M. Heras, Bernard H. Foing
2021	J	`jnl`	Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation. CoRR Alex Cole, Benjamin Kurt Miller, Samuel J. Witte, Maxwell X. Cai, Meiert W. Grootes, Francesco Nattino, Christoph Weniger
2021	A*	`conf`	Truncated Marginal Neural Ratio Estimation. NeurIPS Benjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger
2021	J	`jnl`	Truncated Marginal Neural Ratio Estimation. CoRR Benjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger
2020	J	`jnl`	Finding Symmetry Breaking Order Parameters with Euclidean Neural Networks. CoRR Tess E. Smidt, Mario Geiger, Benjamin Kurt Miller
2020	J	`jnl`	Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties. CoRR Benjamin Kurt Miller, Mario Geiger, Tess E. Smidt, Frank Noé
2020	J	`jnl`	Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time. CoRR Benjamin Kurt Miller, Alex Cole, Gilles Louppe, Christoph Weniger

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.