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Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors
Computer Science > Machine Learning [Submitted on 31 May 2026] Title:Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors View PDF HTML (experimental)Abstract:We ask: when do Bayesian model averaging (BMA) weights over decision trees carry sufficient epistemic information to justify committed exploitation of the averaging distribution?
Using Optical Aberrations to Distinguish Real Astronomical Transients
Astrophysics > Instrumentation and Methods for Astrophysics [Submitted on 6 Jun 2026] Title:Fast Astronomical Transients in Archival Photographic Plates: Using optical aberrations as a tool for discerning real images, from plate artifacts View PDF HTML (experimental)Abstract:The detection of fast astronomical transients in photographic plates from the Palomar sky surveys conducted in the 1950s, was subject to the criticism that such transients could be just the effect of otherwise...
Generative Models and Statistical Validation
High Energy Physics - Phenomenology [Submitted on 28 May 2026] Title:Generative Models and Statistical Validation View PDF HTML (experimental)Abstract:Generative machine learning has become an essential tool in theoretical and experimental physics, especially in the context of fast surrogates and density estimators. In this work, we first introduce the underlying framework of modern generative networks and then discuss challenges in quantifying their accuracy, precision, and statistical power.
Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors
Computer Science > Machine Learning [Submitted on 31 May 2026 (v1), last revised 2 Jun 2026 (this version, v2)] Title:Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors View PDF HTML (experimental)Abstract:We ask: when do Bayesian model averaging (BMA) weights over decision trees carry sufficient epistemic information to justify committed exploitation of the averaging distribution?
Do Transformers Need Three Projections? Systematic Study of QKV Variants
Computer Science > Machine Learning [Submitted on 1 Jun 2026] Title:Do Transformers Need Three Projections? Systematic Study of QKV Variants View PDF HTML (experimental)Abstract:Transformers have become the standard solution for various AI tasks, with the query, key, and value (QKV) attention formulation playing a central role.
Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
Computer Science > Machine Learning [Submitted on 1 May 2026 (v1), last revised 21 May 2026 (this version, v2)] Title:Trees to Flows and Back: Unifying Decision Trees and Diffusion Models View PDFAbstract:Decision trees and diffusion models are ostensibly disparate model classes, one discrete and hierarchical, the other continuous and dynamic. This work unifies the two by establishing a crisp mathematical correspondence between hierarchical decision trees and diffusion processes in...
Generative Models and Statistical Validation
High Energy Physics - Phenomenology [Submitted on 28 May 2026] Title:Generative Models and Statistical Validation View PDF HTML (experimental)Abstract:Generative machine learning has become an essential tool in theoretical and experimental physics, especially in the context of fast surrogates and density estimators. In this work, we first introduce the underlying framework of modern generative networks and then discuss challenges in quantifying their accuracy, precision, and statistical power.
Can LLMs Beat Classical Hyperparameter Optimization Algorithms?
Computer Science > Machine Learning [Submitted on 25 Mar 2026 (v1), last revised 17 Apr 2026 (this version, v5)] Title:Can LLMs Beat Classical Hyperparameter Optimization Algorithms?
Variational free complement method with Gaussian-expanded complement functions: convergence with fixed Gaussian expansion length
Physics > Chemical Physics [Submitted on 1 Jun 2026] Title:Variational free complement method with Gaussian-expanded complement functions: convergence with fixed Gaussian expansion length View PDF HTML (experimental)Abstract:For the free complement theory with Gaussian-expanded complement functions, the energy convergence of $n_\mathrm{G} = \mathrm{constant} < \infty, n\rightarrow\infty$ is discussed, where $n_\mathrm{G}$ is the number of the Gaussian functions in the STO-$n$G expansion.
Unsupervised Learning Based Focal Stack Camera Depth Estimation
Electrical Engineering and Systems Science > Image and Video Processing [Submitted on 14 Mar 2022 (v1), last revised 3 Jun 2026 (this version, v3)] Title:Unsupervised Learning Based Focal Stack Camera Depth Estimation View PDFAbstract:We propose an unsupervised deep learning based method to estimate depth from focal stack camera images. On the NYU-v2 dataset, our method achieves much better depth estimation accuracy compared to single-image based methods.