Variational Free Energy
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Related Articles from SNS
Variational Free Energy Pivot Selection for Pivoted Cholesky
arXiv:2606.01821v1 Announce Type: new Abstract: Pivoted Cholesky factorizations construct low-rank approximations of symmetric positive definite matrices by sequentially selecting pivots from the residual diagonal. Classical greedy and randomized rules, such as randomly pivoted Cholesky, target the algebraic trace-norm error of the residual. In many applications, however, the matrix enters a nonlinear matrix functional whose value, not the trace-norm error, determines solution quality, and...
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.
What Type of Inference is Active Inference?
Announce Type: new Abstract: Active inference casts decision-making as inference, with the Expected Free Energy (EFE) unifying goal-directed and information-seeking behavior. Recent work showed that EFE minimization can be written as Variational Free Energy (VFE) minimization on a generative model augmented with epistemic priors. We prove that the VFE of the augmented model can be rewritten as the VFE of the predictive model plus explicit entropy-correction terms, making the EFE contribution...
VEDAL: Variational Error-Driven Asynchronous Learning for 3D Gaussian Splatting Pruning
Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) achieves remarkable novel view synthesis quality with real-time rendering, yet suffers from excessive memory consumption due to millions of Gaussian primitives. Existing pruning methods rely on heuristic importance scores or synchronous batch updates, leading to suboptimal compression and training instability. We propose VEDAL, a principled framework that formulates Gaussian pruning as variational free energy minimization.
Universal Extremum Seeking Mechanism for Lift Variation in Soaring Birds Flight: A New Paradigm in Computational Physics and Biology
arXiv:2605.20232v2 Announce Type: replace Abstract: In this letter, we reveal a universal, very simple extremum seeking natural feedback law and mechanism that governs, adapts, and generates in real-time, optimized lift variations for successful energy gain flight in presence of wind shear. The introduced law/mechanism, which is computationally minimal and needs only sensory information of the wind or local energy rate (i.e., model-free and data-driven) is able to characterize and replicate...
Quantitative Nonequilibrium Pathway from Fundamental Physics to the Emergence and Persistence of Exoplanetary Biospheres
arXiv:2606.02648v1 Announce Type: new Abstract: We present a physics-based framework that runs from fundamental interactions and constants to biospheres, using a sequence of quantitative nonequilibrium thresholds ("gates"). Each gate is an inequality in measurable variables-free-energy flux, reaction-transport rates, replication fidelity, coding capacity, ecological closure, and climate feedback gains. Crucially, the gate vector is anchored in fundamental physics: dimensionless constants,...
BRAIN: Bayesian Reasoning via Active Inference for Agentic and Embodied Intelligence in Mobile Networks
arXiv:2602.14033v1 Announce Type: cross Abstract: Future sixth-generation (6G) mobile networks will demand artificial intelligence (AI) agents that are not only autonomous and efficient, but also capable of real-time adaptation in dynamic environments and transparent in their decisionmaking. However, prevailing agentic AI approaches in networking, exhibit significant shortcomings in this regard.
Possible dark matter-deficient twins discovered in the Fornax Cluster
June 9, 2026 report Possible dark matter-deficient twins discovered in the Fornax Cluster Shreejaya Karantha Author Gaby Clark Scientific Editor Robert Egan Associate Editor Astronomers have identified a possible new example of one of the universe's strangest galaxy types: galaxies that appear to contain little or no dark matter. The newly studied pair, FCC 224 and FCC 240, on the outskirts of the Fornax Cluster, share several unusual traits with the only known pair of controversial...
Optimal velocity fields for instantaneous magnetic field growth
arXiv:2508.03573v3 Announce Type: replace Abstract: We consider a variant of the kinematic dynamo problem. Rather than prescribing a velocity field and searching for high-growth magnetic fields via an eigenvalue problem, we treat the seed magnetic-field structure as given and ask which velocity field maximally enhances its instantaneous growth. We show this second problem has an elegant formulation in terms of variational calculus.
A 65 nm Multi-Modal Bayesian Inference Engine with 16.3 fJ/Sample Calibration-Free GRNG for Risk-Aware At-Home Skin Lesion Screening
arXiv:2606.07439v1 Announce Type: new Abstract: We present a 65-nm risk-aware multimodal Bayesian inference engine for privacy-preserving, fully on-device skin lesion screening under uncontrolled at-home conditions. The proposed compute-in-memory architecture performs in-word Mixture-of-Gaussian sampling, improving uncertainty modeling beyond conventional unimodal Bayesian neural networks. This added probabilistic expressiveness increases equal-risk operating coverage by 1.4x, improves...