SuperAnimal pretrained pose estimation models for behavioral analysis

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Current progress in artificial intelligence is centered around so-called large language models that consist of neural networks processing long sequences of high-dimensional vectors called tokens. Statistical physics provides powerful tools to study the fun ...

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 ...

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 ...

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 ...

With the significant increase in photovoltaic (PV) electricity generation, more attention has been given to PV power forecasting. Indeed, accurate forecasting allows power grid operators to better schedule and dispatch their assets, such as energy storage ...

Reasoning about distance is indispensable for establishing or avoiding contact in manipulation tasks. To this end, we present an online approach for learning implicit representations of signed distance using piecewise polynomial basis functions. Starting f ...

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, ...

SuperAnimal pretrained pose estimation models for behavioral analysis

Chattez avec Graph Search

FADE: Forecasting for anomaly detection on ECG

Anomaly Anything: Promptable Unseen Visual Anomaly Generation

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

Pose-Invariant Face Recognition via Feature-Space Pose Frontalization

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

GraphOntology Dataset

Nonparametric network summaries

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

Multi-Objective Management for Many-Core Computing Servers

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

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

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

Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-Dimensional Tokens

Fundamental Social Learning Scaling Law for Tracking Hidden Markov Models

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

Discovering meaningful units from text sequences

Intraday solar irradiance forecasting using public cameras

Online Learning of Continuous Signed Distance Fields Using Piecewise Polynomials

Towards Robust Vision Models