.- Solving Two-Stage Stochastic Programming problems via Machine Learning.
.- Weight-varying Model Predictive Control for Coupled Cyber-Physical Systems: Aerial Grasping Study.
.- Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach.
.- Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services.
.- Protein Sequence Generation using Denoising Probabilistic Diffusion Model.
.- Individual Fairness in Generative Text Models.
.- Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs.
.- Artificial Intelligence and Cyber Security.
.- Exploring Digital Health Trends in the Headlines via Knowledge Graph Analysis.
.- Robust Infidelity: When Faithfulness Measures on Masked Language Models Are Misleading.
.- Optimal risk scores for continuous predictors.
.- Post-Treatment Gait Prediction after Botulinum Toxin Injections Using Deep Learning with an Attention Mechanism.
.- Leveraging Graph Networks and Generative Adversarial Networks for Controllable Trajectory Prediction.
.- Nearest Neighbors Counterfactuals.
.- An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning.
.- Pattern detection in abnormal district heating data.
.- Harnessing Graph Neural Networks for Pattern Classification in Heterogeneous Event Graphs.
.- Learn to Create Neighborhoods in Real-World Vehicle Routing Problem.
.- PointerKex: A Pointer-based SSH Key Extraction method.
.- Addressing The Permutation Flowshop Scheduling with Grey Wolf Optimizer.
.- MCGRAN: Multi-Conditional Graph Generation for Neural Architecture Search.
.- Generative reward machine for Reinforcement learning for Physical Internet Distribution Centre.
.- Between accurate prediction and poor decision making: the AI/ML gap.
.- Cross-Metapath based Hashing for Recommendation Systems.
.- Beyond Iterative Tuning: Zero-Shot Hyperparameter Optimisation for Decision Trees.
.- Augmented Human-AI Forecasting for Ship Refit Project Scheduling: A Predict-then-Optimize Approach.
.- Evaluation of Document Deduplication Algorithms for Large Text Corpora.
.- Hicks Traverse meets One-Factor SVM: Belief Incoherence Attractors.
.- Synthetic Time Series for Anomaly Detection in Cloud Microservices.
.- Radiotherapy Treatment Planning: An Integrated Optimization and Reinforcement
Learning Approach.
.- Leap: Inductive Link Prediction via Learnable Topology Augmentation.
.- Estimating Completeness of Consensus Models: Geometrical and Distributional Approaches.
.- Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines.
.- Clarifying the Fog: Evaluating and Enhancing User Comprehension of Android Data Safety Documents.
