Saved in:
| Main Authors: | Polson, Nick, Sokolov, Vadim |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.20575 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Fast Compute via MC Boosting
by: Polson, Sarah, et al.
Published: (2026)
by: Polson, Sarah, et al.
Published: (2026)
Counting $N$ Queens
by: Polson, Nick, et al.
Published: (2024)
by: Polson, Nick, et al.
Published: (2024)
Bayesian Double Descent
by: Polson, Nick, et al.
Published: (2025)
by: Polson, Nick, et al.
Published: (2025)
Fast Compute for ML Optimization
by: Polson, Nick, et al.
Published: (2026)
by: Polson, Nick, et al.
Published: (2026)
Generative Bayesian Computation as a Scalable Alternative to Gaussian Process Surrogates
by: Polson, Nick, et al.
Published: (2026)
by: Polson, Nick, et al.
Published: (2026)
Generative Quantile Bayesian Prediction
by: Nareklishvili, Maria, et al.
Published: (2025)
by: Nareklishvili, Maria, et al.
Published: (2025)
Generative Bayesian Hyperparameter Tuning
by: Lopes, Hedibert, et al.
Published: (2025)
by: Lopes, Hedibert, et al.
Published: (2025)
Generative Modeling: A Review
by: Nareklishvili, Maria, et al.
Published: (2024)
by: Nareklishvili, Maria, et al.
Published: (2024)
Generative Bayesian Computation for Maximum Expected Utility
by: Polson, Nick, et al.
Published: (2024)
by: Polson, Nick, et al.
Published: (2024)
Horseshoe Priors and MDP
by: Polson, Nick, et al.
Published: (2026)
by: Polson, Nick, et al.
Published: (2026)
Bell's Inequality, Causal Bounds, and Quantum Bayesian Computation: A Unified Framework
by: Polson, Nick, et al.
Published: (2026)
by: Polson, Nick, et al.
Published: (2026)
Negative Probability
by: Polson, Nick, et al.
Published: (2024)
by: Polson, Nick, et al.
Published: (2024)
Synthetic Priors
by: Polson, Nick, et al.
Published: (2026)
by: Polson, Nick, et al.
Published: (2026)
Horseshoe Mixtures-of-Experts (HS-MoE)
by: Polson, Nick, et al.
Published: (2026)
by: Polson, Nick, et al.
Published: (2026)
Kolmogorov GAM Networks are all you need!
by: Polson, Sarah, et al.
Published: (2025)
by: Polson, Sarah, et al.
Published: (2025)
Bayesian Methods for the Navier-Stokes Equations
by: Polson, Nicholas, et al.
Published: (2026)
by: Polson, Nicholas, et al.
Published: (2026)
Generative AI for Bayesian Computation
by: Polson, Nicholas G., et al.
Published: (2023)
by: Polson, Nicholas G., et al.
Published: (2023)
Bayesian Global-Local Regularization
by: Datta, Jyotishka, et al.
Published: (2025)
by: Datta, Jyotishka, et al.
Published: (2025)
Photons = Tokens: The Physics of AI and the Economics of Knowledge
by: Litowitz, Alec, et al.
Published: (2026)
by: Litowitz, Alec, et al.
Published: (2026)
Kramnik vs Nakamura: A Chess Scandal
by: Maharaj, Shiva, et al.
Published: (2024)
by: Maharaj, Shiva, et al.
Published: (2024)
Some Bayesian Perspectives on Clinical Trials
by: Sokolova, Alexandra, et al.
Published: (2026)
by: Sokolova, Alexandra, et al.
Published: (2026)
Generative AI for Validating Physics Laws
by: Nareklishvili, Maria, et al.
Published: (2025)
by: Nareklishvili, Maria, et al.
Published: (2025)
Generative Causal Inference
by: Nareklishvili, Maria, et al.
Published: (2023)
by: Nareklishvili, Maria, et al.
Published: (2023)
Merging two cultures: Deep and statistical learning
by: Anindya Bhadra, et al.
Published: (2024)
by: Anindya Bhadra, et al.
Published: (2024)
Bayes Risk for Goodness of Fit Tests
by: Polson, Nicholas G., et al.
Published: (2026)
by: Polson, Nicholas G., et al.
Published: (2026)
Bayes, E-values and Testing
by: Polson, Nicholas G., et al.
Published: (2026)
by: Polson, Nicholas G., et al.
Published: (2026)
An Old Look at Empirical Bayes
by: Polson, Nicholas G., et al.
Published: (2026)
by: Polson, Nicholas G., et al.
Published: (2026)
Conformal Prediction = Bayes?
by: Datta, Jyotishka, et al.
Published: (2025)
by: Datta, Jyotishka, et al.
Published: (2025)
A New Look at Bayesian Testing
by: Datta, Jyotishka, et al.
Published: (2026)
by: Datta, Jyotishka, et al.
Published: (2026)
Solving Fuzzy Satisfiability via Mixed-Integer Non-Linear Programming
by: Castro, Pablo F.
Published: (2026)
by: Castro, Pablo F.
Published: (2026)
A Mixed-Integer Linear Programming (MILP) for Garment Line Balancing
by: Kong, Ray Wai Man, et al.
Published: (2025)
by: Kong, Ray Wai Man, et al.
Published: (2025)
Minimum Carbon Trusses: Constructible Multi-Component Designs with Mixed-Integer Linear Programming
by: Schemmer, Zane Hallowell, et al.
Published: (2026)
by: Schemmer, Zane Hallowell, et al.
Published: (2026)
Optimization Modulo Integer Linear-Exponential Programs
by: Hitarth, S, et al.
Published: (2025)
by: Hitarth, S, et al.
Published: (2025)
Intermittent Rendezvous Plans with Mixed Integer Linear Program for Large-Scale Multi-Robot Exploration
by: da Silva, Alysson Ribeiro, et al.
Published: (2025)
by: da Silva, Alysson Ribeiro, et al.
Published: (2025)
FMIP: Joint Continuous-Integer Flow For Mixed-Integer Linear Programming
by: Li, Hongpei, et al.
Published: (2025)
by: Li, Hongpei, et al.
Published: (2025)
Efficient Workload Balancing on Heterogeneous GPUs using Mixed-Integer Non-Linear Programming
by: Chih-Sheng Lin
Published: (2014)
by: Chih-Sheng Lin
Published: (2014)
Alternative Mixed Integer Linear Programming Optimization for Joint Job Scheduling and Data Allocation in Grid Computing
by: Feng, Shengyu, et al.
Published: (2025)
by: Feng, Shengyu, et al.
Published: (2025)
Integer Linear-Exponential Programming in NP by Quantifier Elimination
by: Chistikov, Dmitry, et al.
Published: (2024)
by: Chistikov, Dmitry, et al.
Published: (2024)
GPU-Accelerated Primal Heuristics for Mixed Integer Programming
by: Çördük, Akif, et al.
Published: (2025)
by: Çördük, Akif, et al.
Published: (2025)
Constrained C-Test Generation via Mixed-Integer Programming
by: Lee, Ji-Ung, et al.
Published: (2024)
by: Lee, Ji-Ung, et al.
Published: (2024)
Similar Items
-
Fast Compute via MC Boosting
by: Polson, Sarah, et al.
Published: (2026) -
Counting $N$ Queens
by: Polson, Nick, et al.
Published: (2024) -
Bayesian Double Descent
by: Polson, Nick, et al.
Published: (2025) -
Fast Compute for ML Optimization
by: Polson, Nick, et al.
Published: (2026) -
Generative Bayesian Computation as a Scalable Alternative to Gaussian Process Surrogates
by: Polson, Nick, et al.
Published: (2026)