Key papers

• Audited Selective Verification for Risk-Controlled N-1 Thermal Contingency Screening under Deployment Shift (2026)
  Jayakumar Manoharan
  4.39
• Is the Statistical Advantage Worth the Cost? An Empirical Comparison of KANs and MLPs for Structured Data Classification (2026)
  Matthew Steven P. Toledo et al.
  4.39
• Temperature Scaling Is Not Enough: Calibration Gaps Under Human Label Distributions (2026)
  Wisdom Dogah
  4.39
• PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference (2026)
  Xutao Wang et al.
  4.39
• Clustering algorithms for multivariate wind farm SCADA data filtering (2026)
  Nicol\`o Italiano et al.
  4.39
• Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule (2026)
  Ahmed Cherif
  4.39
• From biodiversity modelling to conservation action: a spatial indicator for prioritising tropical forest protection, restoration, and management (2026)
  Ma\"iri Souza Oliveira et al.
  4.39
• Scaling Laws for Classical Machine Learning on Tabular Data: A Benchmark Study (2026)
  Kaihua Ding
  4.39
• An Insight on Evaluation Metrics Under the Imbalanced Case of Anomaly Detection (2026)
  Romain Hermary et al.
  4.39
• Kidney function and kidney failure prediction in a large multiethnic population (2026)
  James A. Diao et al.
  4.39
• An Agnostic Machine Learning Model of Photosynthetic Habitability (2026)
  Callum Gray et al.
  3.45
• Interpretable Anomaly and Drift Detection with Gaussian Mixture Models (2026)
  Behnam Asadi
  2.00
• Archetypes or ability? Clustering for modelling student mathematical competence (2026)
  Benjamin Mawdsley et al.
  2.00
• Optimizing Sensor Placement for Hydrogen Leak Detection in Enclosed Infrastructure: A Comparative Study Using CFD-informed Genetic Algorithm and DeepSets Neural Surrogate (2026)
  Fangnian Wang et al.
  2.00
• Conformal Changepoint Localization and Root Cause Analysis with Corrupted Observations (2026)
  Seunghun Yu et al.
  2.00
• From Unsupervised Subgroups to Hypothetical State-Intervention Policies: An Evaluation of Selected Subgrouping Methods in Observational Health Data (2026)
  Vasundhara Acharya et al.
  2.00
• Enhancing Automated Machine Learning via Homogeneous Train-Test Splitting Methods (2026)
  Yearn Tan Yin Tze et al.
  2.00
• Understanding Context Sampling in TabPFN on Small Tabular Datasets (2026)
  Mohammed Abdullah
  2.00
• Early Failure Prediction from Near-Anomaly Detection: A Proactive Approach (2026)
  L\'ea Billet (LAAS et al.
  2.00
• TreeCCA: Canonical Correlation Analysis via Gradient-Boosted Trees (2026)
  James Chapman
  2.00
• Cost-Sensitive Conformal Prediction and Human-in-the-Loop Abstention for Imbalanced High-Stakes Decision Support: A Multi-Domain Benchmark (2026)
  Manpreet Singh et al.
  2.00
• Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with nonconform (2026)
  Oliver Hennh\"ofer et al.
  1.89
• Calibrate Globally, Measure Everywhere: Scaling LLM-Based Prevalence Measurement Across A/B Experiments (2026)
  Zehao Xu et al.
  1.72
• The Advantage of Fine-Grained Training (2025)
  Davide Pirovano et al.
  1.44
• Differentially Private Permutation Tests (2023)
  Ilmun Kim et al.
  —
• Ask for More Than Bayes Optimal: A Theory of Indecisions for Selective Hypothesis Testing (2024)
  Mohamed Ndaoud et al.
  —