no code implementations • 21 Feb 2024 • Jianqiang Shen, Yuchin Juan, Shaobo Zhang, Ping Liu, Wen Pu, Sriram Vasudevan, Qingquan Song, Fedor Borisyuk, Kay Qianqi Shen, Haichao Wei, Yunxiang Ren, Yeou S. Chiou, Sicong Kuang, Yuan Yin, Ben Zheng, Muchen Wu, Shaghayegh Gharghabi, Xiaoqing Wang, Huichao Xue, Qi Guo, Daniel Hewlett, Luke Simon, Liangjie Hong, Wenjing Zhang
Web-scale search systems typically tackle the scalability challenge with a two-step paradigm: retrieval and ranking.
no code implementations • 19 Dec 2023 • Rebecca M. Crossley, Samuel Johnson, Erika Tsingos, Zoe Bell, Massimiliano Berardi, Margherita Botticelli, Quirine J. S. Braat, John Metzcar, Marco Ruscone, Yuan Yin, Robyn Shuttleworth
The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted.
no code implementations • 9 Oct 2023 • Yuan Yin, Yifei HUANG, Ryosuke Furuta, Yoichi Sato
Point-level supervised temporal action localization (PTAL) aims at recognizing and localizing actions in untrimmed videos where only a single point (frame) within every action instance is annotated in training data.
no code implementations • 25 Jul 2023 • Louis Serrano, Leon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari
For numerical design, the development of efficient and accurate surrogate models is paramount.
1 code implementation • NeurIPS 2023 • Louis Serrano, Lise Le Boudec, Armand Kassaï Koupaï, Thomas X Wang, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari
Machine learning approaches for solving partial differential equations require learning mappings between function spaces.
no code implementations • 9 Jun 2023 • Etienne Le Naour, Louis Serrano, Léon Migus, Yuan Yin, Ghislain Agoua, Nicolas Baskiotis, Patrick Gallinari, Vincent Guigue
We introduce a novel modeling approach for time series imputation and forecasting, tailored to address the challenges often encountered in real-world data, such as irregular samples, missing data, or unaligned measurements from multiple sensors.
no code implementations • 18 Jan 2023 • Carlo Metta, Riccardo Guidotti, Yuan Yin, Patrick Gallinari, Salvatore Rinzivillo
We propose a use case study, for skin lesion diagnosis, illustrating how it is possible to provide the practitioner with explanations on the decisions of a state of the art deep neural network classifier trained to characterize skin lesions from examples.
1 code implementation • 29 Sep 2022 • Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari
Effective data-driven PDE forecasting methods often rely on fixed spatial and / or temporal discretizations.
1 code implementation • 29 Jun 2022 • Léon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari
In this work, we study three multi-resolution schema with integral kernel operators that can be approximated with \emph{Message Passing Graph Neural Networks} (MPGNNs).
1 code implementation • 1 Feb 2022 • Matthieu Kirchmeyer, Yuan Yin, Jérémie Donà, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari
Data-driven approaches to modeling physical systems fail to generalize to unseen systems that share the same general dynamics with the learning domain, but correspond to different physical contexts.
no code implementations • 22 Nov 2021 • Carlo Metta, Andrea Beretta, Riccardo Guidotti, Yuan Yin, Patrick Gallinari, Salvatore Rinzivillo, Fosca Giannotti
A key issue in critical contexts such as medical diagnosis is the interpretability of the deep learning models adopted in decision-making systems.
no code implementations • 26 Aug 2021 • Haoyu Zuo, Yuan Yin, Peter Childs
This paper builds a patent-based knowledge graph, patent-KG, to represent the knowledge facts in patents for engineering design.
1 code implementation • NeurIPS 2021 • Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari
Both are sub-optimal: the former disregards the discrepancies between environments leading to biased solutions, while the latter does not exploit their potential commonalities and is prone to scarcity problems.
2 code implementations • ICLR 2021 • Yuan Yin, Vincent Le Guen, Jérémie Dona, Emmanuel de Bézenac, Ibrahim Ayed, Nicolas Thome, Patrick Gallinari
In this work, we introduce the APHYNITY framework, a principled approach for augmenting incomplete physical dynamics described by differential equations with deep data-driven models.
no code implementations • 25 Sep 2019 • Yuan Yin, Arthur Pajot, Emmanuel de Bézenac, Patrick Gallinari
We tackle the problem of inpainting occluded area in spatiotemporal sequences, such as cloud occluded satellite observations, in an unsupervised manner.
no code implementations • 16 May 2019 • Yuan Yin, Zhewei Wei
Based on the concept of transpose proximity, we design \strap, a factorization based graph embedding algorithm that achieves scalability and non-linearity simultaneously.