ML Fundamentals

From SQL Analytics to Predictive Decision Systems: Operationalizing ML Models in Business Operation

Compliance-Aware Predictive Process Monitoring: A Neuro-Symbolic Approach

On the Relationship between Bayesian Networks and Probabilistic Structural Causal Models

A Multimodal Deep Learning Framework for Edema Classification Using HCT and Clinical Data

Multi-view Graph Convolutional Network with Fully Leveraging Consistency via Granular-ball-based Topology Construction, Feature Enhancement and Interactive Fusion

Ordinal Semantic Segmentation Applied to Medical and Odontological Images

DSO: Dual-Scale Neural Operators for Stable Long-term Fluid Dynamics Forecasting

Dynamic resource matching in manufacturing using deep reinforcement learning

RDEx-SOP: Exploitation-Biased Reconstructed Differential Evolution for Fixed-Budget Bound-Constrained Single-Objective Optimization

RDEx-CSOP: Feasibility-Aware Reconstructed Differential Evolution with Adaptive epsilon-Constraint Ranking

RDEx-MOP: Indicator-Guided Reconstructed Differential Evolution for Fixed-Budget Multiobjective Optimization

Bayes-MICE: A Bayesian Approach to Multiple Imputation for Time Series Data

Multimodal Forecasting for Commodity Prices Using Spectrogram-Based and Time Series Representations

Diagnosing Non-Markovian Observations in Reinforcement Learning via Prediction-Based Violation Scoring

Multiple-Prediction-Powered Inference

Cross-attentive Cohesive Subgraph Embedding to Mitigate Oversquashing in GNNs

What-If Explanations Over Time: Counterfactuals for Time Series Classification

Bit-Identical Medical Deep Learning via Structured Orthogonal Initialization

TwinMixing: A Shuffle-Aware Feature Interaction Model for Multi-Task Segmentation

MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations

Mapping data literacy trajectories in K-12 education

KGroups: A Versatile Univariate Max-Relevance Min-Redundancy Feature Selection Algorithm for High-dimensional Biological Data

A Convex Route to Thermomechanics: Learning Internal Energy and Dissipation

Geometry-aware similarity metrics for neural representations on Riemannian and statistical manifolds

Temporally Detailed Hypergraph Neural ODEs for Disease Progression Modeling

Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks

Efficient Human-in-the-Loop Active Learning: A Novel Framework for Data Labeling in AI Systems

Class-Imbalanced-Aware Adaptive Dataset Distillation for Scalable Pretrained Model on Credit Scoring

A Benchmark for Incremental Micro-expression Recognition

Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement

Measuring the (Un)Faithfulness of Concept-Based Explanations

What Is the Optimal Ranking Score Between Precision and Recall? We Can Always Find It and It Is Rarely $F_1$

Overcoming the Curvature Bottleneck in MeanFlow

Prototype-Based Semantic Consistency Alignment for Domain Adaptive Retrieval

Hellinger Multimodal Variational Autoencoders

Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting

How to Lie with Statistics with your Robot Best Friend

5 Useful Python Scripts for Effective Feature Selection

7 Essential Python Itertools for Feature Engineering