.- 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.
