Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
IEEE

Basket2vec: Learning Retail Basket Representations From Transactional Data

Abstract: In this work, we present the novel basket2vec methodology to learn a rich retail basket representation in a latent space with an aim to preserve the co-occurrence relationship between items.

How do AI coding agents work? We look under the hood.

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

Lemon Slice nabs $10.5M from YC and Matrix to build out its digital avatar tech

Digital avatar generation company Lemon Slice is working to add a video layer to AI chatbots with a new diffusion model that ...
The Marshall Project

How We Cleaned Up and Clarified Federal Data on Deaths in Custody

Data collected under the Death in Custody Reporting Act has some serious problems. Here’s how we fixed some of them.
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
IEEE

Dynamic Graph Regularized Broad Learning With Marginal Fisher Representation for Noisy Data Classification

Abstract: Broad learning system (BLS) is an effective neural network requiring no deep architecture, however it is somehow fragile to noisy data. The previous robust broad models directly map features ...