Patrick Krauss

50 papers A* 1B 3C 1Journal 42Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Convergent Representations of Linguistic Constructions in Human and Artificial Neural Systems. CoRR Pegah Ramezani, Thomas Kinfe, Andreas K. Maier, Achim Schilling, Patrick Krauss
2026	A*	`conf`	Mind in the Machine? Cross-Disciplinary Perceptions of Consciousness in Artificial Intelligence. CHI Hamid Moradi, Ignacio Avellino, Patrick Krauss, Dario Zanca, Ilka Hein, Bjoern M. Eskofier, Madeleine Flaucher
2025	J	`jnl`	Analysis of argument structure constructions in a deep recurrent language model. Frontiers Comput. Neurosci. Pegah Ramezani, Achim Schilling, Patrick Krauss
2025	J	`jnl`	Analysis of argument structure constructions in the large language model BERT. Frontiers Artif. Intell. Pegah Ramezani, Achim Schilling, Patrick Krauss
2025	B	`conf`	Author-Specific Linguistic Patterns Unveiled: A Deep Learning Study on Word Class Distributions. IJCNN Patrick Krauss, Achim Schilling
2025	J	`jnl`	Author-Specific Linguistic Patterns Unveiled: A Deep Learning Study on Word Class Distributions. CoRR Patrick Krauss, Achim Schilling
2025	J	`jnl`	Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT. CoRR Awritrojit Banerjee, Achim Schilling, Patrick Krauss
2025	J	`jnl`	Illuminating the Black Box of Reservoir Computing. CoRR Claus Metzner, Achim Schilling, Thomas Kinfe, Andreas K. Maier, Patrick Krauss
2025	J	`jnl`	Multi-modal cognitive maps for language and vision based on neural successor representations. Neurocomputing Paul Stoewer, Achim Schilling, Pegah Ramezani, Hassane Kissane, Andreas K. Maier, Patrick Krauss
2025	J	`jnl`	Nonlinear Neural Dynamics and Classification Accuracy in Reservoir Computing. Neural Comput. Claus Metzner, Achim Schilling, Andreas K. Maier, Patrick Krauss
2025	J	`jnl`	Probing Internal Representations of Multi-Word Verbs in Large Language Models. CoRR Hassane Kissane, Achim Schilling, Patrick Krauss
2025	J	`jnl`	Probing for consciousness in machines. Frontiers Artif. Intell. Mathis Immertreu, Achim Schilling, Andreas K. Maier, Patrick Krauss
2025	B	`conf`	Refusal Behavior in Large Language Models: A Nonlinear Perspective. IJCNN Fabian Hildebrandt, Andreas K. Maier, Patrick Krauss, Achim Schilling
2025	J	`jnl`	Refusal Behavior in Large Language Models: A Nonlinear Perspective. CoRR Fabian Hildebrandt, Andreas K. Maier, Patrick Krauss, Achim Schilling
2024	J	`jnl`	Analysis and Visualization of Linguistic Structures in Large Language Models: Neural Representations of Verb-Particle Constructions in BERT. CoRR Hassane Kissane, Achim Schilling, Patrick Krauss
2024	J	`jnl`	Analysis of Argument Structure Constructions in a Deep Recurrent Language Model. CoRR Pegah Ramezani, Achim Schilling, Patrick Krauss
2024	J	`jnl`	Analysis of Argument Structure Constructions in the Large Language Model BERT. CoRR Pegah Ramezani, Achim Schilling, Patrick Krauss
2024	J	`jnl`	Analyzing Narrative Processing in Large Language Models (LLMs): Using GPT4 to test BERT. CoRR Patrick Krauss, Jannik Hösch, Claus Metzner, Andreas K. Maier, Peter Uhrig, Achim Schilling
2024	J	`jnl`	Data-driven Modeling in Metrology - A Short Introduction, Current Developments and Future Perspectives. CoRR Linda-Sophie Schneider, Patrick Krauss, Nadine Schiering, Christopher Syben, Richard Schielein, Andreas Maier
2024	J	`jnl`	Deep learning based decoding of single local field potential events. NeuroImage Achim Schilling, Richard Gerum, Claudia Boehm, Jwan Rasheed, Claus Metzner, Andreas Maier, Caroline Reindl, Hajo M. Hamer, Patrick Krauss
2024	—	`conf`	Methodological Considerations in the Analysis of Acoustically Evoked Neural Signals: A Comparative Study of Active EEG, Passive EEG and MEG. EMBC Nikola Kölbl, Konstantin Tziridis, Patrick Krauss, Achim Schilling
2024	J	`jnl`	Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations. CoRR Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss
2024	J	`jnl`	Nonlinear Neural Dynamics and Classification Accuracy in Reservoir Computing. CoRR Claus Metzner, Achim Schilling, Andreas K. Maier, Patrick Krauss
2024	J	`jnl`	Probing for Consciousness in Machines. CoRR Mathis Immertreu, Achim Schilling, Andreas Maier, Patrick Krauss
2024	J	`jnl`	Quantifying and Maximizing the Information Flux in Recurrent Neural Networks. Neural Comput. Claus Metzner, Marius E. Yamakou, Dennis Völkl, Achim Schilling, Patrick Krauss
2024	J	`jnl`	The Early Subcortical Response at the Fundamental Frequency of Speech Is Temporally Separated from Later Cortical Contributions. J. Cogn. Neurosci. Alina Schüller, Achim Schilling, Patrick Krauss, Tobias Reichenbach
2023	J	`jnl`	Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD). CoRR Claus Metzner, Achim Schilling, Patrick Krauss
2023	—	`conf`	Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings. ICDL Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss
2023	J	`jnl`	Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings. CoRR Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss
2023	B	`conf`	Leaky-Integrate-and-Fire Neuron-Like Long-Short-Term-Memory Units as Model System in Computational Biology. IJCNN Richard Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling
2023	J	`jnl`	Quantifying and maximizing the information flux in recurrent neural networks. CoRR Claus Metzner, Marius E. Yamakou, Dennis Völkl, Achim Schilling, Patrick Krauss
2023	C	`conf`	Word class representations spontaneously emerge in a deep neural network trained on next word prediction. ICMLA Kishore Surendra, Achim Schilling, Paul Stoewer, Andreas Maier, Patrick Krauss
2023	J	`jnl`	Word class representations spontaneously emerge in a deep neural network trained on next word prediction. CoRR Kishore Surendra, Achim Schilling, Paul Stoewer, Andreas K. Maier, Patrick Krauss
2022	J	`jnl`	Classification at the Accuracy Limit - Facing the Problem of Data Ambiguity. CoRR Claus Metzner, Achim Schilling, Maximilian Traxdorf, Konstantin Tziridis, Holger Schulze, Patrick Krauss
2022	J	`jnl`	Dynamics and Information Import in Recurrent Neural Networks. Frontiers Comput. Neurosci. Claus Metzner, Patrick Krauss
2022	J	`jnl`	Neural Network based Formation of Cognitive Maps of Semantic Spaces and the Emergence of Abstract Concepts. CoRR Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss
2022	J	`jnl`	Neural Network based Successor Representations of Space and Language. CoRR Paul Stoewer, Christian Schlieker, Achim Schilling, Claus Metzner, Andreas K. Maier, Patrick Krauss
2022	J	`jnl`	Predictive Coding and Stochastic Resonance: Towards a Unified Theory of Auditory (Phantom) Perception. CoRR Achim Schilling, William Sedley, Richard Gerum, Claus Metzner, Konstantin Tziridis, Andreas K. Maier, Holger Schulze, Fan-Gang Zeng, Karl J. Friston, Patrick Krauss
2021	J	`jnl`	Known Operator Learning and Hybrid Machine Learning in Medical Imaging - A Review of the Past, the Present, and the Future. CoRR Andreas Maier, Harald Köstler, Marco Heisig, Patrick Krauss, Seung Hee Yang
2021	—	`conf`	Neural Networks with Fixed Binary Random Projections Improve Accuracy in Classifying Noisy Data. Bildverarbeitung für die Medizin Zijin Yang, Achim Schilling, Andreas Maier, Patrick Krauss
2021	J	`jnl`	Quantifying the separability of data classes in neural networks. Neural Networks Achim Schilling, Andreas Maier, Richard Gerum, Claus Metzner, Patrick Krauss
2020	J	`jnl`	Sparsity through evolutionary pruning prevents neuronal networks from overfitting. Neural Networks Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling
2020	J	`jnl`	Will We Ever Have Conscious Machines? Frontiers Comput. Neurosci. Patrick Krauss, Andreas Maier
2020	J	`jnl`	Will we ever have Conscious Machines? CoRR Patrick Krauss, Andreas Maier
2019	J	`jnl`	Analysis of Structure and Dynamics in Three-Neuron Motifs. Frontiers Comput. Neurosci. Patrick Krauss, Alexandra Zankl, Achim Schilling, Holger Schulze, Claus Metzner
2019	J	`jnl`	Recurrence Resonance" in Three-Neuron Motifs. Frontiers Comput. Neurosci. Patrick Krauss, Karin Prebeck, Achim Schilling, Claus Metzner
2019	J	`jnl`	Sparsity through evolutionary pruning prevents neuronal networks from overfitting. CoRR Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling
2018	J	`jnl`	How deep is deep enough? - Optimizing deep neural network architecture. CoRR Achim Schilling, Jonas Rietsch, Richard Gerum, Holger Schulze, Claus Metzner, Patrick Krauss
2017	J	`jnl`	A Chemical Reaction Network to Generate Random, Power-Law-Distributed Time Intervals. Artif. Life Patrick Krauss, Holger Schulze, Claus Metzner
2015	J	`jnl`	Adaptive stochastic resonance based on output autocorrelations. CoRR Patrick Krauss, Claus Metzner, Konstantin Tziridis, Holger Schulze

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.