Aaron Lou - RankMe

25 papers A* 12Journal 13

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Denoising Diffusion Bridge Models. ICLR Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
2024	A*	`conf`	Diffusion Model Alignment Using Direct Preference Optimization. CVPR Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik
2024	A*	`conf`	Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution. ICML Aaron Lou, Chenlin Meng, Stefano Ermon
2024	A*	`conf`	Equivariant Graph Neural Operator for Modeling 3D Dynamics. ICML Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
2024	J	`jnl`	Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
2024	A*	`conf`	Geometric Trajectory Diffusion Models. NeurIPS Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon
2024	J	`jnl`	Geometric Trajectory Diffusion Models. CoRR Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon
2023	J	`jnl`	Denoising Diffusion Bridge Models. CoRR Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
2023	J	`jnl`	Diffusion Model Alignment Using Direct Preference Optimization. CoRR Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik
2023	J	`jnl`	Discrete Diffusion Language Modeling by Estimating the Ratios of the Data Distribution. CoRR Aaron Lou, Chenlin Meng, Stefano Ermon
2023	A*	`conf`	Reflected Diffusion Models. ICML Aaron Lou, Stefano Ermon
2023	J	`jnl`	Reflected Diffusion Models. CoRR Aaron Lou, Stefano Ermon
2023	A*	`conf`	Riemannian Residual Neural Networks. NeurIPS Isay Katsman, Eric Ming Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher De Sa
2023	J	`jnl`	Riemannian Residual Neural Networks. CoRR Isay Katsman, Eric Ming Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser-Nam Lim, Christopher De Sa
2023	A*	`conf`	Scaling Riemannian Diffusion Models. NeurIPS Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon
2023	J	`jnl`	Scaling Riemannian Diffusion Models. CoRR Aaron Lou, Minkai Xu, Stefano Ermon
2021	A*	`conf`	Equivariant Manifold Flows. NeurIPS Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2021	J	`jnl`	Equivariant Manifold Flows. CoRR Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2021	A*	`conf`	Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. NeurIPS Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli
2021	J	`jnl`	Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. CoRR Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli
2020	A*	`conf`	Differentiating through the Fréchet Mean. ICML Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa
2020	J	`jnl`	Differentiating through the Fréchet Mean. CoRR Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa
2020	A*	`conf`	Neural Manifold Ordinary Differential Equations. NeurIPS Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2020	J	`jnl`	Neural Manifold Ordinary Differential Equations. CoRR Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2018	J	`jnl`	Adversarial Example Decomposition. CoRR Horace He, Aaron Lou, Qingxuan Jiang, Isay Katsman, Pian Pawakapan, Serge J. Belongie, Ser-Nam Lim

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.