Publications related to Bridging structural MRI with cognitive function for individual level classification of early psychosis via deep learning

Related publications (26)

Transferability of Learnt Speech Representations for Decoding Non-Human Vocal Communication

Humans and animals both use acoustic signals for vocal communication. The advent of self-supervised learning (SSL) has enabled neural networks to learn robust and general feature representations through the intrinsic acoustic structure of input signals, wi ...

EPFL2025

Musculoskeletal motor control with reinforcement learning

Alberto Silvio Chiappa

Animals, including humans, interact with the external environment primarily through motion. Replicating their motor control skills in artificial embodied agents is a major objective of artificial intelligence research. This thesis presents a collection of ...

EPFL2025

Intelligent Soft Robotic System for Sensing and Recognition via Triboelectric‐Based Multi‐Sensor Fusion

Xin Chen

Triboelectric nanogenerators (TENGs) serve as a key technology in flexible electronic devices, especially tactile sensors, enabling flexible robotic manipulators to effectively interact with their external environment. Persistent challenges include inadequ ...

Wiley2025

TimeGPT in load forecasting: A large time series model perspective

Fernando Porté Agel, Jiannong Fang, Wenlong Liao

Machine learning models have made significant progress in load forecasting, but their forecast accuracy is limited in cases where historical load data is scarce. Inspired by the outstanding performance of large language models (LLMs) in computer vision and ...

2025

MARBLE: interpretable representations of neural population dynamics using geometric deep learning

Pierre Vandergheynst

The dynamics of neuron populations commonly evolve on low-dimensional manifolds. Thus, we need methods that learn the dynamical processes over neural manifolds to infer interpretable and consistent latent representations. We introduce a representation lear ...

Nature Publishing Group2025

Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion

Olga Fink, Ismail Nejjar

The growing deployment of low-cost, distributed sensor networks in environmental and biomedical domains has enabled continuous, large-scale health monitoring. However, these systems often face challenges related to degraded data quality caused by sensor dr ...

2025

Teaching oxidation states to neural networks

Nicola Marzari

While the accurate description of redox reactions remains a challenge for first-principles calculations, it has been shown that extended Hubbard functionals (DFT+U+V) can provide a reliable approach, mitigating self-interaction errors, in materials with st ...

2025

Learning the language of the genome: AI- and data-driven decoding of genetic variants and disease mechanisms

Ali Saadat Varnosfaderanii

Genetic variation plays a crucial role in human disease susceptibility and molecular pathophysiology. This thesis explores genetic determinants of disease using advanced computational approaches, including statistical modeling, network analysis, and deep l ...

EPFL2025

Detecting mass wasting of Retrogressive Thaw Slumps in spaceborne elevation models using deep learning

Sophia Kublytska

Climate change has led to stronger warming in the Arctic, causing higher ground temperatures and extensive permafrost thaw. Retrogressive Thaw Slumps (RTSs) represent one of the most rapid and considerable geomorphological changes in permafrost regions, oc ...

2025

Foundation neural-networks quantum states as a unified Ansatz for multiple hamiltonians

Luciano Loris Viteritti, Giuseppe Carleo

Foundation models are highly versatile neural-network architectures capable of processing different data types, such as text and images, and generalizing across various tasks like classification and generation. Inspired by this success, we propose Foundati ...

2025

Ensemble learning for portfolio valuation and risk management

Damir Filipovic, Lotfi Boudabsa

We introduce an ensemble learning method for dynamic portfolio valuation and risk management building on regression trees. We learn the dynamic value process of a derivative portfolio from a finite sample of its cumulative cash flow. The estimator is given ...

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD2025

Quantum Differential Privacy in the Local Model

Armando Angrisani

Differential privacy provides a robust framework for protecting sensitive data, while maintaining its utility for computation. In essence, a differentially private algorithm takes as input the data of multiple parties, and returns an output disclosing mini ...

2025

Fingerprints of brain disease: connectome identifiability in Alzheimer’s disease

Dimitri Nestor Alice Van De Ville, Olaf Blanke, Maria Giulia Preti, Enrico Amico, Sara Stampacchia

Functional connectivity patterns in the human brain, like the friction ridges of a fingerprint, can uniquely identify individuals. Does this “brain fingerprint” remain distinct even during Alzheimer’s disease (AD)? Using fMRI data from healthy and patholog ...

Springer Science and Business Media LLC2024

Topics in statistical physics of high-dimensional machine learning

Hugo Chao Cui

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

EPFL2024

Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction

Pascal Frossard, Emmanuel Abbé, Ntorina Thanou, Ortal Yona Senouf, Ivan-Daniel Sievering

Goal: In patients with coronary artery disease, the prediction of future cardiac events such as myocardial infarction (MI) remains a major challenge. In this work, we propose a novel anatomy-informed multimodal deep learning framework to predict future MI ...

2024

The influence of data on adversarial robustness

Javier Alejandro Maroto Morales

Deep learning models are generally vulnerable to small perturbations, raising concerns about safety, security, and performance guarantees. Achieving robustness has been shown to be costly in terms of computational resources and quantity of data. This thesi ...

EPFL2024

Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains

Guillaume Romain Obozinski

Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale ...

San Francisco2024

Impact of Mitofusin 2 in the Nucleus Accumbens on motivated behavior and underlying neurobiological mechanisms

Alessandro Chioino

The nucleus accumbens (NAc) is part of the ventral striatum and plays a major role in motivation and goal-directed behaviour. Increasing evidence implicates impairments in accumbal function in anxiety and depression, two conditions that are commonly accomp ...

EPFL2024

Safety and feasibility of home-based transcranial alternating current stimulation in youths with 22q11.2 deletion syndrome

Silas Forrer

Neurodevelopmental disorders such as attention deficit and/or hyperactivity disorder (ADHD) and schizophrenia are characterized by core impairment in executive functions (EF). Despite the development of various behavioral interventions to enhance EF, the e ...

FRONTIERS MEDIA SA2024

Recursively Feasible Chance-Constrained Model Predictive Control Under Gaussian Mixture Model Uncertainty

Maryam Kamgarpour, Kai Ren

We present a chance-constrained model predictive control (MPC) framework under Gaussian mixture model (GMM) uncertainty. Specifically, we consider the uncertainty that arises from predicting future behaviors of moving obstacles, which may exhibit multiple ...

Institute of Electrical and Electronics Engineers (IEEE)2024