Daniel A. Braun

71 papers A* 1A 2Journal 59Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback. CoRR Zeqiang Zhang, Fabian Wurzberger, Gerrit Schmid, Sebastian Gottwald, Daniel A. Braun
2024	J	`jnl`	Bounded Rational Decision Networks With Belief Propagation. Neural Comput. Gerrit Schmid, Sebastian Gottwald, Daniel A. Braun
2024	J	`jnl`	Countability constraints in order-theoretic approaches to computability. Math. Struct. Comput. Sci. Pedro Hack, Daniel A. Braun, Sebastian Gottwald
2024	J	`jnl`	On the Structure of Information. CoRR Sebastian Gottwald, Daniel A. Braun
2024	J	`jnl`	Online continual learning through unsupervised mutual information maximization. Neurocomputing Heinke Hihn, Daniel A. Braun
2023	J	`jnl`	Automatic Bat Call Classification using Transformer Networks. CoRR Frank Fundel, Daniel A. Braun, Sebastian Gottwald
2023	J	`jnl`	Automatic bat call classification using transformer networks. Ecol. Informatics Frank Fundel, Daniel A. Braun, Sebastian Gottwald
2023	J	`jnl`	Hierarchically structured task-agnostic continual learning. Mach. Learn. Heinke Hihn, Daniel A. Braun
2022	J	`jnl`	Classification of preordered spaces in terms of monotones - Filling in the gaps. CoRR Pedro Hack, Daniel A. Braun, Sebastian Gottwald
2022	J	`jnl`	Computation as uncertainty reduction: a simplified order-theoretic framework. CoRR Pedro Hack, Daniel A. Braun, Sebastian Gottwald
2022	J	`jnl`	Hierarchically Structured Task-Agnostic Continual Learning. CoRR Heinke Hihn, Daniel A. Braun
2022	J	`jnl`	Jarzyski's Equality and Crooks' Fluctuation Theorem for General Markov Chains with Application to Decision-Making Systems. Entropy Pedro Hack, Sebastian Gottwald, Daniel A. Braun
2022	J	`jnl`	On a geometrical notion of dimension for partially ordered sets. CoRR Pedro Hack, Daniel A. Braun, Sebastian Gottwald
2022	J	`jnl`	On the relation of order theory and computation in terms of denumerability. CoRR Pedro Hack, Daniel A. Braun, Sebastian Gottwald
2021	—	`conf`	Binary Classification: Counterbalancing Class Imbalance by Applying Regression Models in Combination with One-sided Label Shifts. ICAART (2) Peter Bellmann, Heinke Hihn, Daniel A. Braun, Friedhelm Schwenker
2021	J	`jnl`	Comparison of short-term electrical load forecasting methods for different building types. Energy Inform. Arne Groß, Antonia Lenders, Friedhelm Schwenker, Daniel A. Braun, David Fischer
2021	J	`jnl`	Mixture-of-Variational-Experts for Continual Learning. CoRR Heinke Hihn, Daniel A. Braun
2021	J	`jnl`	Representing Pareto optima in preordered spaces: from Shannon entropy to injective monotones. CoRR Pedro Hack, Daniel A. Braun, Sebastian Gottwald
2020	J	`jnl`	Binary Classification: Counterbalancing Class Imbalance by Applying Regression Models in Combination with One-Sided Label Shifts. CoRR Peter Bellmann, Heinke Hihn, Daniel A. Braun, Friedhelm Schwenker
2020	J	`jnl`	Specialization in Hierarchical Learning Systems. CoRR Heinke Hihn, Daniel A. Braun
2020	J	`jnl`	Specialization in Hierarchical Learning Systems. Neural Process. Lett. Heinke Hihn, Daniel A. Braun
2020	J	`jnl`	The Two Kinds of Free Energy and the Bayesian Revolution. CoRR Sebastian Gottwald, Daniel A. Braun
2020	J	`jnl`	The two kinds of free energy and the Bayesian revolution. PLoS Comput. Biol. Sebastian Gottwald, Daniel A. Braun
2019	—	`conf`	An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems. CDC Heinke Hihn, Sebastian Gottwald, Daniel A. Braun
2019	J	`jnl`	An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems. CoRR Heinke Hihn, Sebastian Gottwald, Daniel A. Braun
2019	J	`jnl`	Bounded Rational Decision-Making from Elementary Computations That Reduce Uncertainty. Entropy Sebastian Gottwald, Daniel A. Braun
2019	J	`jnl`	Bounded rational decision-making from elementary computations that reduce uncertainty. CoRR Sebastian Gottwald, Daniel A. Braun
2019	J	`jnl`	Hierarchical Expert Networks for Meta-Learning. CoRR Heinke Hihn, Daniel A. Braun
2019	J	`jnl`	Systems of Bounded Rational Agents with Information-Theoretic Constraints. Neural Comput. Sebastian Gottwald, Daniel A. Braun
2018	J	`jnl`	An information-theoretic on-line update principle for perception-action coupling. CoRR Zhen Peng, Tim Genewein, Felix Leibfried, Daniel A. Braun
2018	—	`conf`	Bounded Rational Decision-Making with Adaptive Neural Network Priors. ANNPR Heinke Hihn, Sebastian Gottwald, Daniel A. Braun
2018	J	`jnl`	Bounded Rational Decision-Making with Adaptive Neural Network Priors. CoRR Heinke Hihn, Sebastian Gottwald, Daniel A. Braun
2018	J	`jnl`	Non-Equilibrium Relations for Bounded Rational Decision-Making in Changing Environments. Entropy Jordi Grau-Moya, Matthias Krüger, Daniel A. Braun
2018	J	`jnl`	Systems of bounded rational agents with information-theoretic constraints. CoRR Sebastian Gottwald, Daniel A. Braun
2017	A	`conf`	An information-theoretic on-line update principle for perception-action coupling. IROS Zhen Peng, Tim Genewein, Felix Leibfried, Daniel A. Braun
2016	J	`jnl`	Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations. Biol. Cybern. Tim Genewein, Daniel A. Braun
2016	A	`conf`	Bounded Rational Decision-Making in Feedforward Neural Networks. UAI Felix Leibfried, Daniel A. Braun
2016	—	`conf`	Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes. ECML/PKDD (2) Jordi Grau-Moya, Felix Leibfried, Tim Genewein, Daniel A. Braun
2016	J	`jnl`	Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes. CoRR Jordi Grau-Moya, Felix Leibfried, Tim Genewein, Daniel A. Braun
2015	J	`jnl`	A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker. Neural Comput. Felix Leibfried, Daniel A. Braun
2015	J	`jnl`	Adaptive information-theoretic bounded rational decision-making with parametric priors. CoRR Jordi Grau-Moya, Daniel A. Braun
2015	—	`conf`	Developing neural networks with neurons competing for survival. ICDL-EPIROB Zhen Peng, Daniel A. Braun
2015	J	`jnl`	Information-Theoretic Bounded Rationality. CoRR Pedro A. Ortega, Daniel A. Braun, Justin Dyer, Kee-Eung Kim, Naftali Tishby
2015	J	`jnl`	Structure Learning in Bayesian Sensorimotor Integration. PLoS Comput. Biol. Tim Genewein, Eduard Hez, Zeynab Razzaghpanah, Daniel A. Braun
2014	—	`conf`	Curiosity-driven learning with Context Tree Weighting. ICDL-EPIROB Zhen Peng, Daniel A. Braun
2014	J	`jnl`	Erratum to: Generalized Thompson sampling for sequential decision-making and causal inference. Complex Adapt. Syst. Model. Pedro A. Ortega, Daniel A. Braun
2014	J	`jnl`	Generalized Thompson sampling for sequential decision-making and causal inference. Complex Adapt. Syst. Model. Pedro A. Ortega, Daniel A. Braun
2014	J	`jnl`	Information-Theoretic Bounded Rationality and ε-Optimality. Entropy Daniel A. Braun, Pedro A. Ortega
2014	A*	`conf`	Monte Carlo methods for exact & efficient solution of the generalized optimality equations. ICRA Pedro A. Ortega, Daniel A. Braun, Naftali Tishby
2013	J	`jnl`	Abstraction in decision-makers with limited information processing capabilities. CoRR Tim Genewein, Daniel A. Braun
2013	J	`jnl`	Bounded Rational Decision-Making in Changing Environments. CoRR Jordi Grau-Moya, Daniel A. Braun
2013	J	`jnl`	Generalized Thompson Sampling for Sequential Decision-Making and Causal Inference CoRR Pedro A. Ortega, Daniel A. Braun
2012	J	`jnl`	A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function CoRR Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun
2012	—	`conf`	A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function. NIPS Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun
2012	J	`jnl`	Free Energy and the Generalized Optimality Equations for Sequential Decision Making CoRR Pedro A. Ortega, Daniel A. Braun
2012	J	`jnl`	Risk-Sensitivity in Bayesian Sensorimotor Integration. PLoS Comput. Biol. Jordi Grau-Moya, Pedro A. Ortega, Daniel A. Braun
2011	J	`jnl`	Inferring Visuomotor Priors for Sensorimotor Learning. PLoS Comput. Biol. Edward J. A. Turnham, Daniel A. Braun, Daniel M. Wolpert
2011	J	`jnl`	Information, Utility & Bounded Rationality CoRR Pedro A. Ortega, Daniel A. Braun
2011	J	`jnl`	Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control. Frontiers Comput. Neurosci. Daniel A. Braun, Ad Aertsen, Rony Paz, Eilon Vaadia, Stefan Rotter, Carsten Mehring
2011	—	`conf`	Path integral control and bounded rationality. ADPRL Daniel A. Braun, Pedro A. Ortega, Evangelos A. Theodorou, Stefan Schaal
2010	J	`jnl`	A Minimum Relative Entropy Controller for Undiscounted Markov Decision Processes CoRR Pedro A. Ortega, Daniel A. Braun
2010	—	`conf`	A Minimum Relative Entropy Principle for Adaptive Control in Linear Quadratic Regulators. ICINCO (3) Daniel A. Braun, Pedro A. Ortega
2010	J	`jnl`	A Minimum Relative Entropy Principle for Learning and Acting. J. Artif. Intell. Res. Pedro A. Ortega, Daniel A. Braun
2010	J	`jnl`	An axiomatic formalization of bounded rationality based on a utility-information equivalence CoRR Pedro A. Ortega, Daniel A. Braun
2010	J	`jnl`	Convergence of Bayesian Control Rule CoRR Pedro A. Ortega, Daniel A. Braun
2010	J	`jnl`	Risk-Sensitive Optimal Feedback Control Accounts for Sensorimotor Behavior under Uncertainty. PLoS Comput. Biol. Arne J. Nagengast, Daniel A. Braun, Daniel M. Wolpert
2009	J	`jnl`	A Bayesian Rule for Adaptive Control based on Causal Interventions CoRR Pedro A. Ortega, Daniel A. Braun
2009	J	`jnl`	A conversion between utility and information CoRR Pedro A. Ortega, Daniel A. Braun
2009	J	`jnl`	Nash Equilibria in Multi-Agent Motor Interactions. PLoS Comput. Biol. Daniel A. Braun, Pedro A. Ortega, Daniel M. Wolpert
2009	J	`jnl`	Optimal Control Predicts Human Performance on Objects with Internal Degrees of Freedom. PLoS Comput. Biol. Arne J. Nagengast, Daniel A. Braun, Daniel M. Wolpert
2008	J	`jnl`	A Minimum Relative Entropy Principle for Learning and Acting CoRR Pedro A. Ortega, Daniel A. Braun

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.