Geoffrey Roeder

15 papers A* 3Journal 9Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Local Learning Rules for Out-of-Equilibrium Physical Generative Models. CoRR Cyrill Bösch, Geoffrey Roeder, Marc Serra-Garcia, Ryan P. Adams
2023	—	`conf`	More Stiffness with Less Fiber: End-to-End Fiber Path Optimization for 3D-Printed Composites. SCF Xingyuan Sun, Geoffrey Roeder, Tianju Xue, Ryan P. Adams, Szymon Rusinkiewicz
2022	J	`jnl`	More Stiffness with Less Fiber: End-to-End Fiber Path Optimization for 3D-Printed Composites. CoRR Xingyuan Sun, Geoffrey Roeder, Tianju Xue, Ryan P. Adams, Szymon Rusinkiewicz
2022	J	`jnl`	Provably efficient variational generative modeling of quantum many-body systems via quantum-probabilistic information geometry. CoRR Faris M. Sbahi, Antonio J. Martinez, Sahil Patel, Dmitri Saberi, Jae Hyeon Yoo, Geoffrey Roeder, Guillaume Verdon
2021	A*	`conf`	On Linear Identifiability of Learned Representations. ICML Geoffrey Roeder, Luke Metz, Durk Kingma
2021	J	`jnl`	Probabilistic Graphical Models and Tensor Networks: A Hybrid Framework. CoRR Jacob Miller, Geoffrey Roeder, Tai-Danae Bradley
2020	A*	`conf`	Learning Composable Energy Surrogates for PDE Order Reduction. NeurIPS Alex Beatson, Jordan T. Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams
2020	J	`jnl`	Learning Composable Energy Surrogates for PDE Order Reduction. CoRR Alex Beatson, Jordan T. Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams
2020	J	`jnl`	On Linear Identifiability of Learned Representations. CoRR Geoffrey Roeder, Luke Metz, Diederik P. Kingma
2019	A*	`conf`	Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems. ICML Geoffrey Roeder, Paul K. Grant, Andrew Phillips, Neil Dalchau, Edward Meeds
2019	J	`jnl`	Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems. CoRR Geoffrey Roeder, Paul K. Grant, Andrew Phillips, Neil Dalchau, Edward Meeds
2018	—	`conf`	Backpropagation through the Void: Optimizing control variates for black-box gradient estimation. ICLR (Poster) Will Grathwohl, Dami Choi, Yuhuai Wu, Geoffrey Roeder, David Duvenaud
2017	J	`jnl`	Backpropagation through the Void: Optimizing control variates for black-box gradient estimation. CoRR Will Grathwohl, Dami Choi, Yuhuai Wu, Geoffrey Roeder, David Duvenaud
2017	J	`jnl`	Sticking the Landing: An Asymptotically Zero-Variance Gradient Estimator for Variational Inference. CoRR Geoffrey Roeder, Yuhuai Wu, David Duvenaud
2017	—	`conf`	Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference. NIPS Geoffrey Roeder, Yuhuai Wu, David Duvenaud

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.