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A generic diffusion-based approach for 3D human pose prediction in the wild

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Publications associées (36)

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Streamline RimNet: Tools for Automatic Classification of Paramagnetic Rim Lesions in MRI of Multiple Sclerosis

Joe Najm, Meritxell Bach Cuadra, Cristina Granziera, Francesco La Rosa

This site provides two software tools related to "RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis" by Barquero et al. NeuroImage: Clinical (2020). People using in part or f ...

Zenodo2023

Enhanced Student Learning in Proteomics - an Interactive Tool Support for Teaching Workflows

Kalpani Anuradha Welivita

Teaching and learning support for bioinformatics has become a popular research area. Proteomics education can be bridged with technology enhancements such that tool support for protein structures experiments. Generally, students in proteomics require diffe ...

IEEE2018

Detection and sequence/structure mapping of biophysical constraints to protein variation in saturated mutational libraries and protein sequence alignments with a dedicated server

Matteo Dal Peraro, Luciano Andres Abriata, Christophe Bovigny

Background: Protein variability can now be studied by measuring high-resolution tolerance-to-substitution maps and fitness landscapes in saturated mutational libraries. But these rich and expensive datasets are typically interpreted coarsely, restricting d ...

2016

Meta Transfer Learning for Early Success Prediction in MOOCs

Tanja Christina Käser Jacober, Mirko Marras, Vinitra Swamy

Despite the increasing popularity of massive open online courses (MOOCs), many suffer from high dropout and low success rates. Early prediction of student success for targeted intervention is therefore essential to ensure no student is left behind in a cou ...

ACM2022

Computation and Visualization in Multiscale Modelling of DNA Mechanics

Jaroslaw Glowacki

Amongst the substances found in any living organism one of the most central in the workings of each living cell is deoxyribonucleic acid (DNA). For that reason it has been the subject of research in many of its aspects. These range from DNA sequencing to a ...

EPFL2016

Latent Space Slicing for Enhanced Entropy Modeling in Learning-Based Point Cloud Geometry Compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

The growing adoption of point clouds as an imaging modality has stimulated the search for efficient solutions for compression. Learning-based algorithms have been reporting increasingly better performance and are drawing the attention from the research com ...

IEEE2022

Protein language models trained on multiple sequence alignments learn phylogenetic relationships

Anne-Florence Raphaëlle Bitbol, Damiano Sgarbossa, Umberto Lupo

Self-supervised neural language models with attention have recently been applied to biological sequence data, advancing structure, function and mutational effect prediction. Some protein language models, including MSA Transformer and AlphaFold's EvoFormer, ...

Nature Portfolio2022

How Structural and Physicochemical Determinants Shape Sequence Constraints in a Functional Enzyme

Matteo Dal Peraro, Luciano Andres Abriata

The need for interfacing structural biology and biophysics to molecular evolution is being increasingly recognized. One part of the big problem is to understand how physics and chemistry shape the sequence space available to functional proteins, while sati ...

Public Library Science2015

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Xingchen Yang

Simultaneous prediction of wrist and hand motions is essential for the natural interaction with hand prostheses. In this paper, we propose a novel multi-out Gaussian process (MOGP) model and a multi-task deep learning (MTDL) algorithm to achieve simultaneo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

cgDNA: a software package for the prediction of sequence-dependent coarse-grain free energies of B-form DNA

John Maddocks, Daiva Petkeviciute, Marco Pasi

cgDNA is a package for the prediction of sequence-dependent configuration-space free energies for B-form DNA at the coarse-grain level of rigid bases. For a fragment of any given length and sequence, cgDNA calculates the configuration of the associated fre ...

Oxford Univ Press2014

Extracting phylogenetic dimensions of coevolution reveals hidden functional signals

Anne-Florence Raphaëlle Bitbol

Despite the structural and functional information contained in the statistical coupling between pairs of residues in a protein, coevolution associated with function is often obscured by artifactual signals such as genetic drift, which shapes a protein's ph ...

Nature Portfolio2022

Reduced basis methods for time-dependent problems

Jan Sickmann Hesthaven

Numerical simulation of parametrized differential equations is of crucial importance in the study of real-world phenomena in applied science and engineering. Computational methods for real-time and many-query simulation of such problems often require prohi ...

CAMBRIDGE UNIV PRESS2022

Convex Generalizations of Total Variation Based on the Structure Tensor with Applications to Inverse Problems

Michaël Unser, Stamatios Lefkimmiatis

We introduce a generic convex energy functional that is suitable for both grayscale and vector-valued images. Our functional is based on the eigenvalues of the structure tensor, therefore it penalizes image variation at every point by taking into account t ...

Springer2013

Patch-based methods for variational image processing problems

Emmanuel D'Angelo

Image Processing problems are notoriously difficult. To name a few of these difficulties, they are usually ill-posed, involve a huge number of unknowns (from one to several per pixel!), and images cannot be considered as the linear superposition of a few p ...

EPFL2013

Word-level Embeddings for Cross-Task Transfer Learning in Speech Processing

Pierre Anton Beckmann

Recent breakthroughs in deep learning often rely on representation learning and knowledge transfer. In recent years, unsupervised and self-supervised techniques for learning speech representation were developed to foster automatic speech recognition. Up to ...

EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP2021

Reviewing Challenges of Predicting Protein Melting Temperature Change Upon Mutation Through the Full Analysis of a Highly Detailed Dataset with High-Resolution Structures

Luciano Andres Abriata

Predicting the effects of mutations on protein stability is a key problem in fundamental and applied biology, still unsolved even for the relatively simple case of small, soluble, globular, monomeric, two-state-folder proteins. Many articles discuss the li ...

2021