and fairness in machine learning.Part II - computer vision: classification; and computer vision: 3D methods.Part III - computer vision: anomaly detection; and topics in computer vision.Part IV - brain-inspired computing;

.- Theory of Neural Networks and Machine Learning. .- Multi-label Robust Feature Selection via Subspace-Sparsity Learning. .- Nullspace-based metric for classification of dynamical systems and sensors. .- On the Bayesian Interpretation of Robust Regression Neural Networks. .- Probability-Generating Function Kernels for Spherical Data. .- Tailored Finite Point Operator Networks for Interface problems. .- Novel Methods in Machine Learning. .- A Simple Task-aware Contrastive Local Descriptor Selection Strategy for Few-shot Learning between inter class and intra class. .- Adaptive Compression of the Latent Space in Variational Autoencoders. .- Asymmetric Isomap for Dimensionality Reduction and Data Visualization. .- CALICO: Confident Active Learning with Integrated Calibration. .- Improved Multi-hop Reasoning through Sampling and Aggregating. .- Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks. .- Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations. .- Safe Data Resampling Method based on Counterfactuals Analysis. .- Test-Time Augmentation for Traveling Salesperson Problem. .- Novel Neural Architectures. .- Resonator-Gated RNNs. .- Towards a model of associative memory with learned distributed representations. .- Neural Architecture Search. .- Accelerated NAS via pretrained ensembles and multi-fidelity Bayesian Optimization. .- Feature Activation-Driven Zero-Shot NAS: A Contrastive Learning Framework. .- NAS-Bench-Compre: A Comprehensive Neural Architecture Search Benchmark with Customizable Components. .- NAVIGATOR-D3: Neural Architecture search using VarIational Graph Auto-encoder Toward Optimal aRchitecture Design for Diverse Datasets. .- ResBuilder: Automated Learning of Depth with Residual Structures .- Self-Organization. .- A Neuron Coverage-based Self-Organizing Approach for RBFNNs in Multi-Class Classification Tasks. .- Self-Organising Neural Discrete Representation Learning à la Kohonen. .- Neural Processes. .- Combined Global and Local Information Diffusion of Neural Processes. .- Topology of Neural Processes. .- Novel Architectures for Computer Vision. .- DEEPAM: Toward Deeper Attention Module in Residual Convolutional Neural Networks. .- Differentiable Largest Connected Component Layer for Image Mattin. .- Enhancing Generalization in Convolutional Neural Networks through Regularization with Edge and Line Features. .- Transformer Tracker based on Multi-level Residual Perception Structure. .-Multimodal Architectures. .- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking. .- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation. .- Fairness in Machine Learning. .-  CFP: A Reinforcement Learning Framework for Comprehensive Fairness-Performance Trade-off in Machine Learning.