Relativizing an incompressible number and an incompressible function through subrecursive extensions of Turing machines. - Felipe S. Abrahão (CoRR, 2016)

The "paradox" of computability and a recursive relative version of the Busy Beaver function. - Felipe S. Abrahão (CoRR, 2016)

Emergent Open-Endedness from Contagion of the Fittest. - Felipe S. Abrahão; Klaus Wehmuth; Artur Ziviani (Complex Syst., 2018)

An algorithmically random family of MultiAspect Graphs and its topological properties. - Felipe S. Abrahão; Klaus Wehmuth; Artur Ziviani (CoRR, 2018)

On incompressible high order networks. - Felipe S. Abrahão; Klaus Wehmuth; Artur Ziviani (CoRR, 2018)

Expected Emergence of Algorithmic Information from a Lower Bound for Stationary Prevalence. - Felipe S. Abrahão; Klaus Wehmuth; Artur Ziviani (CoRR, 2018)

Learning the undecidable from networked systems. - Felipe S. Abrahão; Itala M. Loffredo D'Ottaviano; Klaus Wehmuth; Francisco Antonio Doria; Artur Ziviani (CoRR, 2019)

Transtemporal edges and crosslayer edges in incompressible high-order networks. - Felipe S. Abrahão; Klaus Wehmuth; Artur Ziviani (CoRR, 2019)

Algorithmic networks: Central time to trigger expected emergent open-endedness. - Felipe S. Abrahão; Klaus Wehmuth; Artur Ziviani (Theor. Comput. Sci., 2019)

An Algorithmic Information Distortion in Multidimensional Networks. - Felipe S. Abrahão; Klaus Wehmuth; Hector Zenil; Artur Ziviani (COMPLEX NETWORKS (2), 2020)

On the existence of hidden machines in computational time hierarchies. - Felipe S. Abrahão; Klaus Wehmuth; Artur Ziviani (CoRR, 2020)

Emergence of complex data from simple local rules in a network game. - Felipe S. Abrahão; Klaus Wehmuth; Artur Ziviani (CoRR, 2020)

Algorithmic Information Dynamics. - Hector Zenil; Narsis Aftab Kiani; Felipe S. Abrahão; Jesper Tegnér (Scholarpedia, 2020)

Emergence and algorithmic information dynamics of systems and observers. - Felipe S. Abrahão; Hector Zenil (CoRR, 2021)

Algorithmic Probability of Large Datasets and the Simplicity Bubble Problem in Machine Learning. - Felipe S. Abrahão; Hector Zenil; Fábio Porto 001; Klaus Wehmuth (CoRR, 2021)

Algorithmic Information Distortions in Node-Aligned and Node-Unaligned Multidimensional Networks. - Felipe S. Abrahão; Klaus Wehmuth; Hector Zenil; Artur Ziviani (Entropy, 2021)

Optimal Spatial Deconvolution and Message Reconstruction from a Large Generative Model of Models. - Hector Zenil; Alyssa M. Adams; Felipe S. Abrahão (CoRR, 2023)

The simplicity bubble effect as a zemblanitous phenomenon in learning systems. - Felipe S. Abrahão; Ricardo P. Cavassane; Michael Winter; Itala M. Loffredo D'Ottaviano (CoRR, 2023)

The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence. - Hector Zenil; Jesper Tegnér; Felipe S. Abrahão; Alexander Lavin; Vipin Kumar 001; Jeremy G. Frey; Adrian Weller; Larisa N. Soldatova; Alan R. Bundy; Nicholas R. Jennings; Koichi Takahashi; Lawrence Hunter; et al. (CoRR, 2023)

Assembly Theory is an approximation to algorithmic complexity based on LZ compression that does not explain selection or evolution. - Felipe S. Abrahão; Santiago Hernández-Orozco; Narsis A. Kiani; Jesper Tegnér; Hector Zenil (CoRR, 2024)

Decoding Geometric Properties in Non-Random Data from First Information-Theoretic Principles. - Hector Zenil; Felipe S. Abrahão (CoRR, 2024)

Assembly Theory Reduced to Shannon Entropy and Rendered Redundant by Naive Statistical Algorithms. - Luan Ozelim; Abicumaran Uthamacumaran; Felipe S. Abrahão; Santiago Hernández-Orozco; Narsis A. Kiani; Jesper Tegnér; Hector Zenil (CoRR, 2024)

On Sequential Structures in Incompressible Multidimensional Networks. - Felipe S. Abrahão; Klaus Wehmuth; Hector Zenil; Artur Ziviani (Parallel Process. Lett., 2024)

Minimal algorithmic information loss methods for dimension reduction, feature selection and network sparsification. - Hector Zenil; Narsis A. Kiani; Alyssa M. Adams; Felipe S. Abrahão; Antonio Rueda-Toicen; Allan A. Zea; Luan Ozelim; Jesper Tegnér (Inf. Sci., 2025)

SuperARC: A Test for General and Super Intelligence Based on First Principles of Recursion Theory and Algorithmic Probability. - Alberto Hernández-Espinosa; Luan Ozelim; Felipe S. Abrahão; Hector Zenil (CoRR, 2025)

Neurodivergent Influenceability as a Contingent Solution to the AI Alignment Problem. - Alberto Hernández-Espinosa; Felipe S. Abrahão; Olaf Witkowski; Hector Zenil (CoRR, 2025)

Binarized Neural Networks Converge Toward Algorithmic Simplicity: Empirical Support for the Learning-as-Compression Hypothesis. - Eduardo Yuji Sakabe; Felipe S. Abrahão; Alexandre da Silva Simões; Esther Colombini; Paula Dornhofer Paro Costa; Ricardo R. Gudwin; Hector Zenil (CoRR, 2025)