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- Hierarchical clustering of X-Ray Fluorescence images using a dissimilarity based on the likelihood ratio statistic
- Non-asymptotic Convergence of Average-reward Q-learning with Options
- Des indices de prix en pleine rénovation
- Zaïre : un Institut dévasté... mais il reste les statisticiens !
- DIAL, développement d'investigations sur l'ajustement à long terme
- L'ENSAE et les relations internationales
- Les relations internationales du Département de la recherche et du CREST
- Le CESD et la formation des statisticiens africains
- Pour des échanges télématiques avec l'extérieur l'Insee utilise TEDECO
- Une interface DDS / SAS au service de la fiabilité des traitements
- Changepoint detection methods as a practical tool for assessment of ecological restoration
- Consequences of COVID-19 infection on educators’ executive functions: A systematic review and meta-analysis protocol
- Study on radiation damage of tungsten-based targets induced by deuterium ions
- Contrasting offshore and onshore strong ground motions from the 2025 Mw 7.6 Aomori subduction interface earthquake: Characteristics and model evaluation
- Multidimensional analysis of social discourse on Twitter (X) around Venezuelan migration in Colombia
- Reservoir dynamic evolution and drainage optimization in deep saturated coalbed methane of Shenfu Block
- Does a historical catch record support a stable latent structure in catch composition across ports, taxa, and years? An assessment of cooperative-level catch statistics from Lake Biwa, Japan, 1962–1972
- Orientability of Causal Relations in Time Series using Summary Causal Graphs and Faithful Distributions
- Local markov equivalence for pc-style local causal discovery and identification of controlled direct effects
- Multi-Sensitive Distributional Fairness: Joint Wasserstein Audits and Shapley Allocation
- Generalizing Identifiability Results in Causal Discovery from Complete Data to Missing Data Settings
- Embedding Geometry Shapes LLM Routing: Tracing Failure Modes and Improving Generalization
- Student Copula Markov Networks
- Neural Supervised Clustering for Learning Individualized Treatment Rules with Many Treatments
- Theoretical and Practical Advances in Hierarchical Bayesian Deep Learning Methodology