Cover Image

Bayesian Modeling of Collatz Stopping Times: A Probabilistic Machine Learning Perspective

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bonacorsi, Nicolò, Bordoni, Matteo
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Probability Statistics Theory Applications 62F15(Primary), 60G40 62J12 65C05 68T05 (Secondary) G.3; I.2.6; I.6.8
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Machine Collaboration
by: Liu, Qingfeng, et al.
Published: (2021)

Signature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting
by: Redhead, Benjamin R., et al.
Published: (2026)

Adaptive Mixture Importance Sampling for Automated Ads Auction Tuning
by: Jia, Yimeng, et al.
Published: (2024)

Multirate Stein Variational Gradient Descent for Efficient Bayesian Sampling
by: Sarshar, Arash
Published: (2026)

Multiple data-driven missing imputation
by: Kavun, Sergii
Published: (2025)

G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration
by: Holt, Samuel, et al.
Published: (2025)

Classifier Calibration at Scale: An Empirical Study of Model-Agnostic Post-Hoc Methods
by: Manokhin, Valery, et al.
Published: (2026)

Throwing Vines at the Wall: Structure Learning via Random Search
by: Vatter, Thibault, et al.
Published: (2025)

Towards the Best Solution for Complex System Reliability: Can Statistics Outperform Machine Learning?
by: Gamiz, Maria Luz, et al.
Published: (2024)

Comparing EPGP Surrogates and Finite Elements Under Degree-of-Freedom Parity
by: Amo, Obed, et al.
Published: (2025)

Synthetic data for ratemaking: imputation-based methods vs adversarial networks and autoencoders
by: Havrylenko, Yevhen, et al.
Published: (2025)

Inductive Venn-Abers and related regressors
by: Petej, Ivan, et al.
Published: (2026)

Aggregation in conformal e-classification
by: Vovk, Vladimir
Published: (2026)

Pair Correlation Factor and the Sample Complexity of Gaussian Mixtures
by: Aryan, Farzad
Published: (2025)

Intra-tree Column Subsampling Hinders XGBoost Learning of Ratio-like Interactions
by: Pinchuk, Mykola
Published: (2026)

A General Framework for Off-Policy Learning with Partially-Observed Reward
by: Takehi, Rikiya, et al.
Published: (2025)

OML-AD: Online Machine Learning for Anomaly Detection in Time Series Data
by: Wette, Sebastian, et al.
Published: (2024)

Factorizable joint shift revisited
by: Tasche, Dirk
Published: (2026)

Leveraging Machine Learning for Official Statistics: A Statistical Manifesto
by: Puts, Marco, et al.
Published: (2024)

Constant-Target Energy Matching: A Unified Framework for Continuous and Discrete Density Estimation
by: Zeng, Zhijun, et al.
Published: (2026)

Forecasting Oncology Demand Trends with Boosting-Based Bayesian Conjugate Models
by: Neto, Ademir Batista dos Santos, et al.
Published: (2026)

From 'What-is' to 'What-if' in Human-Factor Analysis: A Post-Occupancy Evaluation Case
by: Chen, Xia, et al.
Published: (2025)

Quantile Additive Trend Filtering
by: Zhang, Zhi, et al.
Published: (2023)

Real-Time Anomaly Detection with Synthetic Anomaly Monitoring (SAM)
by: Luzio, Emanuele, et al.
Published: (2025)

TimeGraph: Synthetic Benchmark Datasets for Robust Time-Series Causal Discovery
by: Ferdous, Muhammad Hasan, et al.
Published: (2025)

MMD-Balls as Credal Sets: A PAC-Bayesian Framework for Epistemic Uncertainty in Test-Time Adaptation
by: Ariq, Ahanaf Hasan
Published: (2026)

Multi-Hypothesis Prediction for Portfolio Optimization: A Structured Ensemble Learning Approach to Risk Diversification
by: Dominguez, Alejandro Rodriguez, et al.
Published: (2025)

Quantile-Scaled Bayesian Optimization Using Rank-Only Feedback
by: Egunjobi, Tunde Fahd
Published: (2025)

metabeta -- A fast neural model for Bayesian mixed-effects regression
by: Kipnis, Alex, et al.
Published: (2025)

SplitWise Regression: Stepwise Modeling with Adaptive Dummy Encoding
by: Kurbucz, Marcell T., et al.
Published: (2025)

Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation
by: Xie, Runlong, et al.
Published: (2026)

FBMS: An R Package for Flexible Bayesian Model Selection and Model Averaging
by: Frommlet, Florian, et al.
Published: (2025)

Variance-Reduced Diffusion Sampling via Target Score Identity
by: Duston, Alois, et al.
Published: (2026)

Augmented Functional Random Forests: Classifier Construction and Unbiased Functional Principal Components Importance through Ad-Hoc Conditional Permutations
by: Maturo, Fabrizio, et al.
Published: (2024)

Jacobian-Velocity Bounds for Deployment Risk Under Covariate Drift
by: Landers, Jonathan R.
Published: (2026)

Optimization-Free Topological Sort for Causal Discovery via the Schur Complement of Score Jacobians
by: Wu, Rui, et al.
Published: (2026)

Deterministic Coreset Construction via Adaptive Sensitivity Trimming
by: Alpay, Faruk, et al.
Published: (2025)

Optimised Support Vector Regression for California Housing Price Prediction: The Critical Role of Feature Engineering and Hyperparameter Tuning
by: Adutwum, Emmanuel
Published: (2026)

Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration
by: Lin, Shuhang, et al.
Published: (2026)

Prediction-Based Markov Violation Scores for Detecting Non-Markovian Observations in Reinforcement Learning
by: Mysore, Naveen
Published: (2026)