Stein Stabilization
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Related Articles from SNS
Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization
Announce Type: new Abstract: A fundamental tension exists in the large-step inference of diffusion models via their deterministic probability flow ordinary differential equation (PF-ODE) trajectories, which we identify as the contractivity trap: efficient inference favors large step sizes, while aggressive steps and highly expressive denoisers can undermine contraction-based stability certificates for error suppression. To address this, we propose SteinDiff, a step-wise inference-time...
Ranking college football's top 100 newcomers for t...
If the upcoming 2026 college football season is anything like its predecessor, transfer quarterbacks and top freshmen will be crucial for many College Football Playoff runs. And by now, with less than 100 days until the start of the season, we can assess rosters and what players did during spring practice with their new teams. While we have analyzed the top newcomer for each Power 4 team, these rankings are regardless of teams.
TASER: Task-Aware Stein Regularisation for Geometry-Driven Robustness
Announce Type: new Abstract: Modern deep networks remain fragile under distribution shift and adversarial perturbations, often due to excessive or poorly structured input sensitivity. We introduce TASER (Task-Aware Stein Regularisation), a training-time regularisation framework derived from Langevin Stein operators. By penalising pointwise Stein residuals under the training distribution, TASER encourages geometric compatibility between predictors and data density, inducing anisotropic,...
Reinforcement Learning for Flow-Matching Policies with Density Transport
Announce Type: new Abstract: We present an online reinforcement learning (RL) algorithm for fine-tuning flow-matching policies in continuous-control problems. Our key insight is to view RL-based policy improvement as a transport of action densities towards regions of high reward, which naturally aligns with the transport formulation of flow matching models. Prior methods either approximate the current or optimal policy distribution or resort to distillation, which introduces biased gradients...
Future Power Rankings: How all 68 Power 4 college football teams stack up
Projecting a college football program's future is harder than ever. Rosters and fortunes change dramatically and championship pathways are more open than ever. The assets that make a program great in 2026 might not be there in 2027.