How to reconcile physical theories with the idea of free will: From analysis of a simple model to interval and fuzzy approaches. - Julio C. Urenda; Olga Kosheleva (FUZZ-IEEE, 2008)

Why Spiking Neural Networks Are Efficient: A Theorem. - Michael Beer; Julio C. Urenda; Olga Kosheleva; Vladik Kreinovich (IPMU (1), 2020)

Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria. - Michael Beer; Julio C. Urenda; Olga Kosheleva; Vladik Kreinovich (IPMU (1), 2020)

Natural Invariance Explains Empirical Success of Specific Membership Functions, Hedge Operations, and Negation Operations. - Julio C. Urenda; Orsolya Csiszár; Gábor Csiszár; József Dombi 001; György Eigner; Vladik Kreinovich (NAFIPS, 2020)

How User Ratings Change with Time: Theoretical Explanation of an Empirical Formula. - Julio C. Urenda; Manuel Hernandez; Natalia Villanueva-Rosales; Vladik Kreinovich (NAFIPS, 2020)

Why a Classification Based on Linear Approximation to Dynamical Systems Often Works Well in Nonlinear Cases. - Julio C. Urenda; Vladik Kreinovich (NAFIPS, 2020)

How Mathematics and Computing Can Help Fight the Pandemic: Two Pedagogical Examples. - Julio C. Urenda; Olga Kosheleva; Martine Ceberio; Vladik Kreinovich (NAFIPS, 2020)

Why Squashing Functions in Multi-Layer Neural Networks. - Julio C. Urenda; Orsolya Csiszár; Gábor Csiszár; József Dombi 001; Olga Kosheleva; Vladik Kreinovich; György Eigner (SMC, 2020)

Why Kappa Regression? - Julio C. Urenda; Orsolya Csiszár; Gábor Csiszár; József Dombi 001; György Eigner; Olga Kosheleva; Vladik Kreinovich (IFSA/EUSFLAT/AGOP, 2021)

Mexican Folk Arithmetic Algorithm Makes Perfect Sense. - Julio C. Urenda; Christian Servin; Olga Kosheleva; Vladik Kreinovich (NAFIPS, 2021)

Algebraic Approach to Data Processing - Techniques and Applications - Julio C. Urenda; Vladik Kreinovich (Springer, 2022)

Why 1/(1+d) Is an Effective Distance-Based Similarity Measure: Two Explanations. - Julio C. Urenda; Olga Kosheleva; Vladik Kreinovich (IS, 2022)

Fuzzy Techniques, Laplace Indeterminacy Principle, and Maximum Entropy Approach Explain Lindy Effect and Help Avoid Meaningless Infinities in Physics. - Julio C. Urenda; Sean R. Aguilar; Olga Kosheleva; Vladik Kreinovich (Decision Making Under Uncertainty and Constraints, 2023)

Why Homogeneous Membranes Lead to Optimal Water Desalination: A Possible Explanation. - Julio C. Urenda; Martine Ceberio; Olga Kosheleva; Vladik Kreinovich (Decision Making Under Uncertainty and Constraints, 2023)

Why Menzerath's Law? - Julio C. Urenda; Vladik Kreinovich (Uncertainty, Constraints, and Decision Making, 2023)

Dimension Compactification Naturally Follows from First Principles. - Julio C. Urenda; Olga Kosheleva; Vladik Kreinovich (Decision Making Under Uncertainty and Constraints, 2023)

Fuzzy Techniques Explain the Effectiveness of ReLU Activation Function in Deep Learning. - Julio C. Urenda; Olga Kosheleva; Vladik Kreinovich (New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics, 2024)

Why 6-Labels Uncertainty Scale in Geosciences: Probability-Based Explanation. - Aaron Velasco; Julio C. Urenda; Olga Kosheleva; Vladik Kreinovich (New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics, 2024)