Gabriel Kalweit

36 papers A* 7A 2Misc 2Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	BLINK: Behavioral Latent Modeling of NK Cell Cytotoxicity. CoRR Iman Nematollahi, Jose Francisco Villena-Ossa, Alina Moter, Kiana Farhadyar, Gabriel Kalweit, Abhinav Valada, Toni Cathomen, Evelyn Ullrich, Maria Kalweit
2025	—	`conf`	One For All: A Unified Approach to Classification and Self-explanation. MICCAI (14) Mehdi Naouar, Yannick Vogt, Joschka Boedecker, Gabriel Kalweit, Maria Kalweit
2025	J	`jnl`	SR-Reward: Taking The Path More Traveled. CoRR Seyed Mahdi B. Azad, Zahra Padar, Gabriel Kalweit, Joschka Boedecker
2025	J	`jnl`	SR-Reward: Taking The Path More Traveled. Trans. Mach. Learn. Res. Seyed Mahdi B. Azad, Zahra Padar, Gabriel Kalweit, Joschka Boedecker
2025	A*	`conf`	Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification. ICLR Mehdi Naouar, Hanne Raum, Jens Rahnfeld, Yannick Vogt, Joschka Boedecker, Gabriel Kalweit, Maria Kalweit
2024	J	`jnl`	BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design. CoRR Yannick Vogt, Mehdi Naouar, Maria Kalweit, Christoph Cornelius Miething, Justus Duyster, Joschka Boedecker, Gabriel Kalweit
2024	J	`jnl`	Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning. PLoS Comput. Biol. Paul Schmidt-Barbo, Gabriel Kalweit, Mehdi Naouar, Lisa Paschold, Edith Willscher, Christoph Schultheiß, Bruno Märkl, Stefan Dirnhofer, Alexandar Tzankov, Mascha Binder, Maria Kalweit
2024	J	`jnl`	Multi-intention Inverse Q-learning for Interpretable Behavior Representation. Trans. Mach. Learn. Res. Hao Zhu, Brice De La Crompe, Gabriel Kalweit, Artur Schneider, Maria Kalweit, Ilka Diester, Joschka Boedecker
2024	J	`jnl`	Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design. CoRR Yannick Vogt, Mehdi Naouar, Maria Kalweit, Christoph Cornelius Miething, Justus Duyster, Roland Mertelsmann, Gabriel Kalweit, Joschka Boedecker
2023	J	`jnl`	CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations. CoRR Mehdi Naouar, Gabriel Kalweit, Anusha Klett, Yannick Vogt, Paula Silvestrini, Diana Laura Infante Ramírez, Roland Mertelsmann, Joschka Boedecker, Maria Kalweit
2023	J	`jnl`	L(M)V-IQL: Multiple Intention Inverse Reinforcement Learning for Animal Behavior Characterization. CoRR Hao Zhu, Brice De La Crompe, Gabriel Kalweit, Artur Schneider, Maria Kalweit, Ilka Diester, Joschka Boedecker
2023	J	`jnl`	Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles. CoRR Mehdi Naouar, Gabriel Kalweit, Ignacio Mastroleo, Philipp Poxleitner, Marc Christian Metzger, Joschka Boedecker, Maria Kalweit
2022	A*	`conf`	Affordance Learning from Play for Sample-Efficient Policy Learning. ICRA Jessica Borja-Diaz, Oier Mees, Gabriel Kalweit, Lukás Hermann, Joschka Boedecker, Wolfram Burgard
2022	J	`jnl`	Affordance Learning from Play for Sample-Efficient Policy Learning. CoRR Jessica Borja-Diaz, Oier Mees, Gabriel Kalweit, Lukás Hermann, Joschka Boedecker, Wolfram Burgard
2022	A*	`conf`	Deep Surrogate Q-Learning for Autonomous Driving. ICRA Maria Kalweit, Gabriel Kalweit, Moritz Werling, Joschka Boedecker
2022	Misc	`conf`	Latent Plans for Task-Agnostic Offline Reinforcement Learning. CoRL Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram Burgard
2022	J	`jnl`	Latent Plans for Task-Agnostic Offline Reinforcement Learning. CoRR Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram Burgard
2022	—	`—`	On the role of time horizons in reinforcement learning. Gabriel Kalweit
2022	J	`jnl`	Robust and Data-efficient Q-learning by Composite Value-estimation. Trans. Mach. Learn. Res. Gabriel Kalweit, Maria Kalweit, Joschka Boedecker
2021	A*	`conf`	Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. ICRA Branka Mirchevska, Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker
2021	—	`conf`	AnyNets: Adaptive Deep Neural Networks for Medical Data with Missing Values. AI4Function@IJCAI Maria Kalweit, Gabriel Kalweit, Joschka Boedecker
2021	A	`conf`	Q-learning with Long-term Action-space Shaping to Model Complex Behavior for Autonomous Lane Changes. IROS Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker
2020	J	`jnl`	A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis. CoRR Maria Hügle, Gabriel Kalweit, Thomas Huegle, Joschka Boedecker
2020	A*	`conf`	Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video. ICRA Oier Mees, Markus Merklinger, Gabriel Kalweit, Wolfram Burgard
2020	J	`jnl`	Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. CoRR Branka Mirchevska, Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker
2020	A*	`conf`	Deep Inverse Q-learning with Constraints. NeurIPS Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker
2020	J	`jnl`	Deep Inverse Q-learning with Constraints. CoRR Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker
2020	J	`jnl`	Deep Surrogate Q-Learning for Autonomous Driving. CoRR Maria Kalweit, Gabriel Kalweit, Moritz Werling, Joschka Boedecker
2020	A*	`conf`	Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. ICRA Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker
2020	J	`jnl`	Interpretable Multi Time-scale Constraints in Model-free Deep Reinforcement Learning for Autonomous Driving. CoRR Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker
2019	J	`jnl`	Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video. CoRR Oier Mees, Markus Merklinger, Gabriel Kalweit, Wolfram Burgard
2019	A	`conf`	Dynamic Input for Deep Reinforcement Learning in Autonomous Driving. IROS Maria Hügle, Gabriel Kalweit, Branka Mirchevska, Moritz Werling, Joschka Boedecker
2019	J	`jnl`	Dynamic Input for Deep Reinforcement Learning in Autonomous Driving. CoRR Maria Hügle, Gabriel Kalweit, Branka Mirchevska, Moritz Werling, Joschka Boedecker
2019	J	`jnl`	Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. CoRR Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker
2019	J	`jnl`	Off-policy Multi-step Q-learning. CoRR Gabriel Kalweit, Maria Hügle, Joschka Boedecker
2017	Misc	`conf`	Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning. CoRL Gabriel Kalweit, Joschka Boedecker

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.