Conditional
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
DWP full list of Universal Credit support for health conditions
DWP full list of Universal Credit support for health conditions People with certain health conditions may be able to get hundreds more each month People with certain health conditions could be eligible for extra support from Universal Credit. How much they could get may depend on when they told the Department for Work and Pensions of their condition and what their diagnosis actually is. The support can be worth hundreds each month, and is to do with the limited capability for and...
Assessing Sample Quality in Conditional Generation under Compositional Shift
arXiv:2606.09601v1 Announce Type: new Abstract: Conditional generators provide a natural tool for controllable generation, including settings where the desired condition is a new composition of observed attributes or experimental factors. In many applications, especially in scientific domains, such models are attractive to explore conditions for which real samples are rare, expensive, or not yet observed. However, this creates a circularity for evaluation: standard conditional quality...
Expectations vs. Realities: The Cost of MSE-Optimal Forecasting Under Conditional Uncertainty
Announce Type: new Abstract: Multi-step time series forecasting (MSF) is commonly evaluated using point-wise error metrics such as mean squared error (MSE), implicitly treating the conditional mean as a sufficient target. We show that this can be misleading under conditional uncertainty, where the conditional expectation becomes unrepresentative of typical realized values at longer horizons. We formalize this effect through a conditional uncertainty gap and prove that whenever this gap is...
Some drugs 'fail' because of unrealistic testing conditions, scientists discover
Some drugs 'fail' because of unrealistic testing conditions, scientists discover Sadie Harley Scientific Editor Robert Egan Associate Editor A drug once dismissed as ineffective suddenly worked—when scientists tested it under more realistic conditions that mimic the human body. In this surprising new discovery, Northwestern University scientists uncovered a hidden rule of drug behavior. A medicine's effectiveness can change dramatically depending on the conditions inside our cells.
Dynamic Meta-Metrics: Source-Sentence Conditioned Weighting for MT Evaluation
arXiv:2605.09098v2 Announce Type: replace Abstract: We propose Dynamic Meta-Metrics (DMM), a framework for machine translation evaluation that learns source-sentence conditioned combinations of existing metrics. Rather than relying on a single static ensemble or language-specific weighting, DMM adapts the metric combination based on properties of the source segment. We study hard conditioning, which fits an interpretable combiner per cluster, and an exploratory soft-conditioned extension...
A variational formulation of the adjoint Kutta condition in potential flow
arXiv:2606.06937v1 Announce Type: new Abstract: We give a variational formulation of the continuous adjoint Kutta condition for two-dimensional subcritical potential flow, with emphasis on the Kutta condition and the role of the wake. We show that the adjoint Kutta condition can be imposed by a penalty term evaluated at the trailing edge, with the corresponding Lagrange multiplier determined by stationarity of the Lagrangian with respect to circulation, and that a wake treatment is not...
Modeling Stochastic Conditional Dynamics from Sparse Observations via Kernel-Stabilized Flow Matching
arXiv:2411.08314v5 Announce Type: replace Abstract: Learning to transform conditional probability densities over time is a fundamental challenge spanning probabilistic modeling and the natural sciences. This task is paramount when forecasting the evolution of stochastic nonlinear dynamical systems in biological and physical domains. While flow-based models can predict the temporal evolution of probability distributions, existing approaches often assume discrete conditioning with samples that...
Multi-Condition Guided Diffusion Model for Controllable Elastic Parameter Synthesis
arXiv:2606.05751v1 Announce Type: new Abstract: Prestack elastic parameter inversion is important for reservoir characterization and quantitative seismic interpretation. Most existing deep-learning-based methods have achieved promising results, but they generally require sufficient labeled training data and have limited flexibility in integrating multi-source conditioning information. To address this issue, we propose a multi-condition guided diffusion model for controllable elastic...
Condition-Gated Reasoning for Context-Dependent Biomedical Question Answering
arXiv:2602.17911v3 Announce Type: replace Abstract: Current biomedical question answering (QA) systems often assume that medical knowledge applies uniformly, yet real-world clinical reasoning is inherently conditional: nearly every decision depends on patient-specific factors such as comorbidities and contraindications. Existing benchmarks do not evaluate such conditional reasoning, and retrieval-augmented or graph-based methods lack explicit mechanisms to ensure that retrieved knowledge is...
On the Generalization in Topology Optimization via Sensitivity-Conditioned Bernoulli Flow Matching
arXiv:2606.02179v1 Announce Type: new Abstract: Surrogate models for topology optimization (TO) exhibit highly variable out-of-distribution (OOD) generalization under distribution shifts such as changing loads or boundary conditions, yet the source of this variability remains unclear. We hypothesize that OOD performance is governed by how much information the conditioning signal preserves about the adjoint sensitivity (reduced gradient) that drives classical TO. Modeling the TO pipeline as a...