Ralf M. Haefner

13 papers A* 1A 1B 2Journal 5Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Task learning increases information redundancy of neural responses in macaque visual cortex. CoRR Shizhao Liu, Anton Pletenev, Ralf M. Haefner, Adam C. Snyder
2024	J	`jnl`	How does the brain compute with probabilities? CoRR Ralf M. Haefner, Jeffrey M. Beck, Cristina Savin, Mehrdad Salmasi, Xaq Pitkow
2023	—	`conf`	A General Method for Testing Bayesian Models using Neural Data. UniReps Gabor Lengyel, Sabyasachi Shivkumar, Ralf M. Haefner
2022	A	`conf`	Interpolating between sampling and variational inference with infinite stochastic mixtures. UAI Richard D. Lange, Ari S. Benjamin, Ralf M. Haefner, Xaq Pitkow
2022	J	`jnl`	Task-induced neural covariability as a signature of approximate Bayesian learning and inference. PLoS Comput. Biol. Richard D. Lange, Ralf M. Haefner
2021	B	`conf`	A confirmation bias due to approximate active inference. CogSci Ankani Chattoraj, Sabyasachi Shivkumar, Yongsoo Ra, Ralf M. Haefner
2021	J	`jnl`	A confirmation bias in perceptual decision-making due to hierarchical approximate inference. PLoS Comput. Biol. Richard D. Lange, Ankani Chattoraj, Jeffrey M. Beck, Jacob L. Yates, Ralf M. Haefner
2021	J	`jnl`	Interpolating between sampling and variational inference with infinite stochastic mixtures. CoRR Richard D. Lange, Ari S. Benjamin, Ralf M. Haefner, Xaq Pitkow
2021	B	`conf`	Relating confidence judgements to temporal biases in perceptual decision-making. CogSci Ankani Chattoraj, Martynas Snarskis, Ralf M. Haefner
2021	—	`conf`	Tactile motion coordinate transforms in the somatosensory system. WHC Himanshu Ahuja, Ralf M. Haefner, Gregory C. DeAngelis, Manuel Gomez-Ramirez
2018	A*	`conf`	A probabilistic population code based on neural samples. NeurIPS Sabyasachi Shivkumar, Richard D. Lange, Ankani Chattoraj, Ralf M. Haefner
2010	—	`conf`	Evaluating neuronal codes for inference using Fisher information. NIPS Ralf M. Haefner, Matthias Bethge
2008	—	`conf`	An improved estimator of Variance Explained in the presence of noise. NIPS Ralf M. Haefner, Bruce G. Cumming

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.