Evie
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Related Articles from SNS
Bregman meets L\'evy: Stochastic mirror descent with heavy-tailed noise in continuous and discrete time
arXiv:2606.03769v1 Announce Type: cross Abstract: We study the robustness of stochastic mirror descent (SMD) under heavy-tailed noise, focusing on whether the method retains its convergence guarantees when run with infinite-variance stochastic gradient input. To address this question in a principled manner, we begin by introducing a continuous-time model of SMD as a stochastic differential equation (SDE) driven by a centered L\'evy noise process with finite $p$-th order moments, $1 < p \leq...
A Per-Component Diagnostic Protocol for Neural HJB-PIDE Solvers under Control-Dependent L\'evy Jumps
Announce Type: new Abstract: We propose a five-step diagnostic protocol for residual-trained neural HJB-PIDE solvers with control-dependent L\'evy jumps, targeting a general failure mode of neural PDE methods: a learned solution can match headline scalar diagnostics while miscomputing an operator inside its training loss. The protocol pairs each neural solve with at least one from-scratch independent reference, decomposes the Hamiltonian into drift, diffusion, compensator, and...
Approximation of the L\'evy-driven stochastic heat equation on the sphere
Announce Type: replace-cross Abstract: The stochastic heat equation on the sphere driven by an additive square-integra\-ble L\'evy process is approximated by a spectral method in space and forward and backward Euler--Maruyama schemes in time. New regularity results are proven for its solution.
Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning
Announce Type: replace Abstract: Parameter-efficient adaptation of vision-language foundation models is crucial for precise multimodal understanding of biomedical images, yet existing methods remain deterministic and often struggle under domain shift or ambiguous image-text alignment. This limitation is particularly critical in the clinic, where models should remain robust in low-data regimes and domain shifts.
Dance teacher avoids jail after 'prank gone wrong' leaves friend with brain damage
Dance teacher avoids jail after 'prank gone wrong' leaves friend with brain damage The victim was sat with another friend in the boot of Evie Robinson’s Audi A1 when they suddenly fell out as the then 19-year-old drove across a car park in Mansfield A dance teacher has narrowly avoided jail after her 18-year-old friend suffered horrific brain injuries falling out of the boot of her car in a "prank" which went wrong. The victim was sat with another friend in the boot of Evie Robinson’s Audi...
Decomposition of Anomalous Diffusion in two-state random walks
arXiv:2606.00149v1 Announce Type: cross Abstract: Two-state stochastic models, where motion alternates between distinct dynamical modes, are widely observed in complex systems. Here we study the Two-State Random Walk (TSRW), which switches between a continuous-time random walk (CTRW) rest state and a standard L'evy walk (LW) motion state, each with power-law distributed sojourn times. Using anomalous diffusion decomposition, we show that TSRWs exhibit a generic coexistence of Joseph...
Decomposition of Anomalous Diffusion in two-state random walks
Announce Type: replace-cross Abstract: Two-state stochastic models, where motion alternates between distinct dynamical modes, are widely observed in complex systems. Here we study the Two-State Random Walk (TSRW), which switches between a continuous-time random walk (CTRW) rest state and a standard L'evy walk (LW) motion state, each with power-law distributed sojourn times.
Why has Belfast erupted in anti-immigrant violence after a knife attack?
Why has Belfast erupted in anti-immigrant violence after a knife attack? Ministers have blamed far-right online agitators for stoking racial tension following a stabbing. Anti-immigration protests have broken out in Belfast, Northern Ireland, after a knife attack allegedly perpetrated by a Sudanese refugee left the country on edge.
Fourier fractal dimension to predict the generalization of deep neural networks
arXiv:2606.08308v1 Announce Type: new Abstract: Predicting the generalization performance of deep neural networks without relying on hold-out validation data is a fundamental challenge in machine learning. While Stochastic Gradient Descent (SGD) drives the optimization of these highly parameterized models, its heavy-tailed, non-Gaussian dynamics induce complex, scale-invariant trajectories in the parameter space.
Wave Resistance for Stochastic Motion at Interfaces
Announce Type: cross Abstract: Wave resistance is the drag generated by the wave radiation that a source moving at a fluid interface sustains. Under stochastic trajectories, the mean drag is controlled by the ensemble-averaged surface profile built from the trajectory history.