Publications associées à Limite d'une suite

Generative power of a protein language model trained on multiple sequence alignments

Anne-Florence Raphaëlle Bitbol, Umberto Lupo, Damiano Sgarbossa

Computational models starting from large ensembles of evolutionarily related protein sequences capture a representation of protein families and learn constraints associated to protein structure and function. They thus open the possibility for generating no ...

eLIFE SCIENCES PUBL LTD2023

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

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan

Predicting 3D human poses in real-world scenarios, also known as human pose forecasting, is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and occlusions. To address these challenges, we propose a diffusion-based approach th ...

IEEE2023

cgNA+: A sequence-dependent coarse-grain model of double-stranded nucleic acids

Rahul Sharma

DNA mechanics plays a crucial role in many biological processes, including nucleosome positioning and protein-DNA interactions. It is believed that nature employs epigenetic modifications in DNA to further regulate gene expression. Moreover, double-strande ...

EPFL2023

Maximum Radiation Efficiency of an Implantable Antenna: The Role of High-Order Modes

Anja Skrivervik, Mingxiang Gao, Jakub Liska

A combination of two numerical techniques of computational electromagnetics, namely, method of moments and vector spherical wave expansion, is used to show performance limitations on the radiation efficiency of implantable antennas and to efficiently resol ...

IEEE2023

Learning to Align Sequential Actions in the Wild

Pascal Fua, Bugra Tekin, Weizhe Liu

State-of-the-art methods for self-supervised sequential action alignment rely on deep networks that find correspon- dences across videos in time. They either learn frame-to- frame mapping across sequences, which does not leverage temporal information, or a ...

IEEE COMPUTER SOC2022

Strong Subconvexity for Self-Dual GL(3) L-Functions

Yongxiao Lin, Ramon Moreira Nunes, Zhi Qi

In this paper, we prove strong subconvexity bounds for self-dual GL(3) L-functions in the t-aspect and for GL(3) x GL(2) L-functions in the GL(2)-spectral aspect. The bounds are strong in the sense that they are the natural limit of the moment method pione ...

OXFORD UNIV PRESS2022

Probing multi-particle unitarity with the Landau equations

Miguel Alexandre Ribeiro Correia, Alexander Zhiboedov, Amit Sever

We consider the 2 -> 2 scattering amplitude of identical massive particles. We identify the Landau curves in the multi-particle region 16m(2)

2022

Functional peaks-over-threshold analysis

Anthony Christopher Davison, Raphaël Gérard Théodore Michel Marie de Deloÿe et Fourcade de Fondeville

Peaks-over-threshold analysis using the generalised Pareto distribution is widely applied in modelling tails of univariate random variables, but much information may be lost when complex extreme events are studied using univariate results. In this paper, w ...

WILEY2022

Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy

Nicolas Boumal

We consider the problem of provably finding a stationary point of a smooth function to be minimized on the variety of bounded-rank matrices. This turns out to be unexpectedly delicate. We trace the difficulty back to a geometric obstacle: On a nonsmooth se ...

SPRINGER HEIDELBERG2022

A Rosetta-based protein design protocol converging to natural sequences

Bruno Emanuel Ferreira De Sousa Correia, Stéphane Rosset, Zander Harteveld, Giulia Sormani

Computational protein design has emerged as a powerful tool capable of identifying sequences compatible with pre-defined protein structures. The sequence design protocols, implemented in the Rosetta suite, have become widely used in the protein engineering ...

AMER INST PHYSICS2021