Publications related to GenPolar: Generative AI-Aided Complexity Reduction for Polar SCL Decoding

Related publications (9)

Nonparametric network summaries

This thesis is concerned with improving the interpretability of network summaries in both a theoretical and an applied framework, with an application to clinically relevant problems in neuroscience. The theoretical part of this thesis is concerned with gra ...

EPFL2025

From Prediction to Prescription: Machine Learning and Causal Inference for the Heterogeneous Treatment Effect

Elise Hélène Dumas

The increasing accumulation of medical data brings the hope of data-driven medical decision-making, but data's increasing complexity—as text or images in electronic health records—calls for complex models, such as machine learning. Here, we review how mach ...

Annual Reviews2025

GraphOntology Dataset

Francisco Pereira Correia Pinto, Ramtin Yazdanian

The EPFL Graph Platform is an open-source data infrastructure designed for academic institutions. It organizes educational and institutional data into a semantically interconnected knowledge graph, making it accessible through a graph-based search engine a ...

Zenodo2025

Assessing workflow impact and clinical utility of AI-assisted brain aneurysm detection: A multi-reader study

Meritxell Bach Cuadra

Despite the plethora of AI-based algorithms developed for anomaly detection in radiology, subsequent integration into clinical setting is rarely evaluated. In this work, we assess the applicability and utility of an AI-based model for brain aneurysm detect ...

2025

BlueCelluLab: Biologically Detailed Neural Network Experimentation API

Henry Markram, Eilif Benjamin Muller, Werner Alfons Hilda Van Geit, Lida Kanari, Mustafa Anil Tuncel, Darshan Mandge, Aurélien Tristan Jaquier

The NEURON simulator, established in 1984 and continuously developed since, stands as the preeminent tool for neuron simulation within computational neuroscience. Its widespread adoption and compatibility with computational clusters and supercomputers unde ...

The Open Journal2024

Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar, Guillaume Marc Georges Vray, Devavrat Tomar

Developing computational pathology models is essential for reducing manual tissue typing from whole slide images, transferring knowledge from the source domain to an unlabeled, shifted target domain, and identifying unseen categories. We propose a practica ...

Institute of Electrical and Electronics Engineers2024

Discovering meaningful units from text sequences

Melika Behjati

In recent years, the field of Natural Language Processing has seen significant revolution by the introduction of Transformers, a stack of multiple layers of attention and non-linearity, capable of performing almost any task and the backbone for large found ...

EPFL2024

Prompt-guided and multimodal landscape scenicness assessments with vision-language models

Devis Tuia

Recent advances in deep learning and Vision-Language Models (VLM) have enabled efficient transfer to downstream tasks even when limited labelled training data is available, as well as for text to be directly compared to image content. These properties of V ...

PUBLIC LIBRARY SCIENCE2024

Towards Robust Vision Models

Harshitha Machiraju

Deep convolutional neural networks (DCNNs) have significantly advanced the field of computer vision and are often considered as plausible models for the human visual system. However, they still have several vulnerabilities in terms of adversarial attacks, ...

EPFL2024