Unsupervised Controllable Generation with Self-Training

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Holography enables quantitative phase sensing through light wave interference, allowing interesting imaging modalities applied in computational microscopy where phase shift is used as a way to generate image contrast. Recovering both amplitude and phase di ...

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 ...

Background and Objective: Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early and accurate detection to improve patient outcomes. Taking advantage of advances in machine learning and deep learning, multiple app ...

We study the large-scale dynamics of the solution to a nonlinear stochastic heat equation (SHE) in dimensions d≥3 with long-range dependence. This equation is driven by multiplicative Gaussian noise, which is white in time and coloured in space with non-in ...

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 ...

Visual anomaly detection (AD) presents significant challenges due to the scarcity of anomalous data samples. While numerous works have been proposed to synthesize anomalous samples, these synthetic anomalies often lack authenticity or require extensive tra ...

Pose-invariant face recognition has become a challenging problem for modern AI-based face recognition systems. It aims at matching a profile face captured in the wild with a frontal face registered in a database. Existing methods perform face frontalizatio ...

In recent decades, the rapid growth of cloud computing has transformed the technological landscape and profoundly impacted our daily lives, driven by the demand for secure, flexible, and cost-effective computing solutions. To meet these demands, computing ...

This paper studies the problem of interconnected agents collaborating to track a dynamic state from partially informative observations, where the dynamic state evolves according to a slowly varying finite-state Markov chain. Although the centralized versio ...

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 ...

Throughout history, pandemics have profoundly impacted societies, underscoring the need for effective public health interventions. The recent COVID-19 pandemic highlighted the importance of Non-Pharmaceutical Interventions (NPIs) in controlling disease tra ...

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 ...

Cross-view localization, the task of estimating a camera's 3-degrees-of-freedom (3-DoF) pose by aligning ground-level images with satellite images, is crucial for large-scale outdoor applications like autonomous navigation and augmented reality. Existing m ...

Identification of spot-like structures in large, noisy microscopy images is a crucial step for many life-science applications. Imaging-based spatial transcriptomics (iST), in particular, relies on the precise detection of millions of transcripts in low sig ...

Since the 1960s, the prevalence of pollen allergy has increased worldwide in developed countries and this trend is continuing, exacerbated by climate change. In the 20th century, operational pollen monitoring networks have been set-up to respond to the nee ...

Interfacing artificial devices with the human brain is the central goal of neurotechnology. Yet, our imaginations are often limited by currently available paradigms and technologies. Suggestions for brain-machine interfaces have changed over time, along wi ...

The CRC-aided successive cancellation list (CA-SCL) decoding algorithm for polar codes has gained widespread adoption thanks to its outstanding performance. However, with the evolution of 6G technologies, the high complexity of CA-SCL decoding poses a chal ...

we were captivated by the opportunities and challenges of integrating robots into education, and collectively, we shared a deep enthusiasm for their potential to revolutionize social robotics in meaningful ways. ...

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 ...

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 ...

Unsupervised Controllable Generation with Self-Training

Chattez avec Graph Search

Cross-Net: Joint In-Line Holographic Image Reconstruction and Refocusing

Nonparametric network summaries

FADE: Forecasting for anomaly detection on ECG

Fluctuations of stochastic PDEs with long-range correlations

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

Anomaly Anything: Promptable Unseen Visual Anomaly Generation

Pose-Invariant Face Recognition via Feature-Space Pose Frontalization

Multi-Objective Management for Many-Core Computing Servers

Fundamental Social Learning Scaling Law for Tracking Hidden Markov Models

GraphOntology Dataset

Epidemic Management: Integrating Behavioral, Mobility, and Epidemiological Perspectives

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

GeoDistill: Geometry-Guided Self-Distillation for Weakly Supervised Cross-View Localization

Spotiflow: accurate and efficient spot detection for fluorescence microscopy with deep stereographic flow regression

Automatic identification of atmospheric bioaerosol using real-time imaging and fluorescence

Interfacing with the Brain: How Nanotechnology Can Contribute

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

Editorial: Advances in robots for learning

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

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