Oscar Key - RankMe

16 papers A* 3A 1Journal 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Composite Goodness-of-fit Tests with Kernels. J. Mach. Learn. Res. Oscar Key, Arthur Gretton, François-Xavier Briol, Tamara Fernandez
2025	J	`jnl`	TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models. CoRR Léo Grinsztajn, Klemens Flöge, Oscar Key, Felix Birkel, Philipp Jund, Brendan Roof, Benjamin Jäger, Dominik Safaric, Simone Alessi, Adrian Hayler, Mihir Manium, Rosen Yu, Felix Jablonski, Shi Bin Hoo, Anurag Garg, Jake Robertson, Magnus Bühler, Vladyslav Moroshan, Lennart Purucker, Clara Cornu, Lilly Charlotte Wehrhahn, Alessandro Bonetto, Bernhard Schölkopf, Sauraj Gambhir, Noah Hollmann, Frank Hutter
2024	J	`jnl`	Approximate Top- CoRR Oscar Key, Luka Ribar, Alberto Cattaneo, Luke Hudlass-Galley, Douglas Orr
2024	J	`jnl`	Scalable Data Assimilation with Message Passing. CoRR Oscar Key, So Takao, Daniel Giles, Marc Peter Deisenroth
2023	A*	`conf`	No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models. NeurIPS Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner
2023	J	`jnl`	No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models. CoRR Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner
2023	A*	`conf`	Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference. ICML Ayush Bharti, Masha Naslidnyk, Oscar Key, Samuel Kaski, François-Xavier Briol
2022	J	`jnl`	Interlocking Backpropagation: Improving depthwise model-parallelism. J. Mach. Learn. Res. Aidan N. Gomez, Oscar Key, Kuba Perlin, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal
2022	J	`jnl`	Towards Healing the Blindness of Score Matching. CoRR Mingtian Zhang, Oscar Key, Peter Hayes, David Barber, Brooks Paige, François-Xavier Briol
2021	J	`jnl`	Composite Goodness-of-fit Tests with Kernels. CoRR Oscar Key, Tamara Fernandez, Arthur Gretton, François-Xavier Briol
2021	A	`conf`	Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties. AISTATS Lisa Schut, Oscar Key, Rory McGrath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal
2021	J	`jnl`	Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties. CoRR Lisa Schut, Oscar Key, Rory McGrath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal
2021	J	`jnl`	Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression. CoRR Joost van Amersfoort, Lewis Smith, Andrew Jesson, Oscar Key, Yarin Gal
2021	A*	`conf`	On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes. ICML Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth
2020	J	`jnl`	Interlocking Backpropagation: Improving depthwise model-parallelism. CoRR Aidan N. Gomez, Oscar Key, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal
2020	J	`jnl`	On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes. CoRR Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth

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.