- Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications.- Contextual Data Augmentation for Task-Oriented Dialog Systems.- Fairness of ChatGPT and the Role Of Explainable-Guided Prompts.- Deep learning meets Neuromorphic Hardware.- Non-Dissipative Propagation by Randomized Anti-Symmetric Deep Graph Networks.- On the Noise Robustness of Analog Complex-Valued Neural Networks.- Neu-BrAuER: a neuromorphic Braille letters audio-reader for commercial edge devices.- Discovery challenge.

- Transductive Fire-affected Area Segmentation with False-Color Data.- Post Wildfire Burnt-up Detection using Siamese UNet.- Predicting Exoplanetary Features with a Residual Model for Uniform and Gaussian Distributions.- Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model.- Simulation-based Inference for Exoplanet Atmospheric Retrieval: Insights from winning the Ariel Data Challenge 2023 using Normalizing Flows.- ITEM: IoT, Edge, and Mobile for Embedded Machine Learning.- Implications of Noise in Resistive Memory on Deep Neural Networks for Image Classification.- Evaluating custom-precision operator support in MLIR for ARM CPUs.

- microYOLO: Towards Single-Shot Object Detection on Microcontrollers.- OptiSim: A Hardware-Aware Optimization Space Exploration Tool for CNN Architectures.- On the Non-Associativity of Analog Computations.- Quantized dynamics models for hardware-efficient control and planning in model-based RL.- LIMBO - LearnIng and Mining for BlOckchains.- Temporal and Geographical Analysis of Real Economic Activities in the Bitcoin Blockchain.- Machine Learning for Cybersecurity (MLCS 2023).- A source separation approach to temporal graph modelling for computer networks.

- Quantum Machine Learning for Malware Classification.- Side-channel Based Intrusion Detection for Network Equipment.- I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models.- Concept Drift Detection using Ensemble of Integrally Private Models.- MIDAS - The 8th Workshop on MIning DAta for financial applicationS.- ViBERTgrid BiLSTM-CRF: Multimodal Key Information Extraction from Unstructured Financial Documents.- Comparing Deep RL and Traditional Financial Portfolio Methods - Full paper.- Occupational Fraud Detection through Agent-based Data Generation.

- Stock Price Time Series Forecasting Using Dynamic Graph Neural Networks and Attention Mechanism in Recurrent Neural Networks.- Flexible Tails for Normalising Flows, with Application to the Modelling of Financial Return Data.- Exploring Alternative Data for Nowcasting: A Case Study on US GDP using Topic Attention.- Topology-Agnostic Detection of Temporal Money Laundering Flows in Billion-Scale Transactions.- Boosting Credit Risk Data Quality using Machine Learning and eXplainable AI Techniques.- Ensemble methods for Stock Market Prediction.- Workshop on Advancements in Federated Learning.- Federated Learning with Neural Graphical Models.

- On improving accuracy in Federated Learning using GANs-based pre-training and Ensemble Learning.- Re-evaluating the Privacy Benefit of Federated Learning.- Parameterizing Federated Continual Learning for Reproducible Research.