Sorbonne Université

research

∙ 12/29/2019

Deep Context-Aware Kernel Networks

Context plays a crucial role in visual recognition as it provides comple...

Mingyuan Jiu, et al. ∙

research

∙ 10/01/2019

Exploring Self-Assembling Behaviors in a Swarm of Bio-micro-robots using Surrogate-Assisted MAP-Elites

Swarms of molecular robots are a promising approach to create specific s...

Leo Cazenille, et al. ∙

research

∙ 04/28/2020

Small-Task Incremental Learning

Lifelong learning has attracted much attention, but existing works still...

Arthur Douillard, et al. ∙

research

∙ 05/13/2020

Novelty Search makes Evolvability Inevitable

Evolvability is an important feature that impacts the ability of evoluti...

Stéphane Doncieux, et al. ∙

research

∙ 02/15/2018

Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays

During sleep and awake rest, the hippocampus replays sequences of place ...

Lise Aubin, et al. ∙

research

∙ 06/21/2018

Topological Data Analysis Made Easy with the Topology ToolKit

This tutorial presents topological methods for the analysis and visualiz...

Guillaume Favelier, et al. ∙

research

∙ 07/14/2018

Piecewise Deterministic Markov Processes and their invariant measure

Piecewise Deterministic Markov Processes (PDMPs) are studied in a genera...

Alain Durmus, et al. ∙

research

∙ 08/17/2018

Lifted Wasserstein Matcher for Fast and Robust Topology Tracking

This paper presents a robust and efficient method for tracking topologic...

Maxime Soler, et al. ∙

research

∙ 10/18/2018

First-order and second-order variants of the gradient descent: a unified framework

In this paper, we provide an overview of first-order and second-order va...

Thomas Pierrot, et al. ∙

research

∙ 11/20/2018

Convergence rate of optimal quantization grids and application to empirical measure

We study the convergence rate of optimal quantization for a probability ...

Yating Liu, et al. ∙

research

∙ 11/27/2018

eXclusive Autoencoder (XAE) for Nucleus Detection and Classification on Hematoxylin and Eosin (H&E) Stained Histopathological Images

In this paper, we introduced a novel feature extraction approach, named ...

Chao-Hui Huang, et al. ∙

research

∙ 01/03/2019

From exploration to control: learning object manipulation skills through novelty search and local adaptation

Programming a robot to deal with open-ended tasks remains a challenge, i...

Seungsu Kim, et al. ∙

research

∙ 04/11/2019

Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata

News agencies produce thousands of multimedia stories describing events ...

Charlotte Rudnik, et al. ∙

research

∙ 06/25/2019

Stabilization of infinite-dimensional linear control systems by POD reduced-order Riccati feedback

There exist many ways to stabilize an infinite-dimensional linear autono...

Emmanuel Trélat, et al. ∙

research

∙ 09/12/2019

Unsupervised Learning and Exploration of Reachable Outcome Space

Performing Reinforcement Learning in sparse rewards settings, with very ...

Paolo Giuseppe, et al. ∙

research

∙ 09/19/2019

Highlighting Bias with Explainable Neural-Symbolic Visual Reasoning

Many high-performance models suffer from a lack of interpretability. The...

Adrien Bennetot, et al. ∙

research

∙ 09/26/2019

Ephemeral instruments

This article questions the notion of ephemerality of digital musical ins...

Vincent Goudard, et al. ∙

research

∙ 09/15/2019

State Representation Learning from Demonstration

In a context where several policies can be observed as black boxes on di...

Astrid Merckling, et al. ∙

research

∙ 11/14/2019

Solving Inverse Problems by Joint Posterior Maximization with a VAE Prior

In this paper we address the problem of solving ill-posed inverse proble...

Mario González, et al. ∙

research

∙ 12/05/2019

Turnpike in optimal shape design

We introduce and study the turnpike property for time-varying shapes, wi...

Gontran Lance, et al. ∙

research

∙ 12/12/2019

Totally Deep Support Vector Machines

Support vector machines (SVMs) have been successful in solving many comp...

Hichem Sahbi, et al. ∙

research

∙ 12/31/2019

Mathematical Analysis of Robustness of Two-Level Domain Decomposition Methods with respect to Inexact Coarse Solves

Convergence of domain decomposition methods rely heavily on the efficien...

Frédéric Nataf, et al. ∙

research

∙ 01/11/2020

On Polynomial Modular Number Systems over Z/pZ

Polynomial Modular Number System (PMNS) is a convenient number system fo...

Jean Claude Bajard, et al. ∙

research

∙ 03/20/2020

Analysis of the SORAS domain decomposition preconditioner for non-self-adjoint or indefinite problems

We analyze the convergence of the one-level overlapping domain decomposi...

Marcella Bonazzoli, et al. ∙

research

∙ 04/15/2020

Explaining Regression Based Neural Network Model

Several methods have been proposed to explain Deep Neural Network (DNN)....

Mégane Millan, et al. ∙

research

∙ 04/15/2020

ActionSpotter: Deep Reinforcement Learning Framework for Temporal Action Spotting in Videos

Summarizing video content is an important task in many applications. Thi...

Guillaume Vaudaux-Ruth, et al. ∙

research

∙ 04/16/2020

MobiAxis: An Embodied Learning Task for Teaching Multiplication with a Social Robot

The use of robots in educational settings is growing increasingly popula...

Karen Tatarian, et al. ∙

research

∙ 04/24/2020

High performance SIMD modular arithmetic for polynomial evaluation

Two essential problems in Computer Algebra, namely polynomial factorizat...

Pierre Fortin, et al. ∙

research

∙ 05/14/2020

Reproducibility of Parallel Preconditioned Conjugate Gradient in Hybrid Programming Environments

The Preconditioned Conjugate Gradient method is often employed for the s...

Roman Iakymchuk, et al. ∙

research

∙ 06/15/2020

Linear functional regression with truncated signatures

We place ourselves in a functional regression setting and propose a nove...

Adeline Fermanian, et al. ∙

research

∙ 06/08/2020

Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects

We present new insights into causal inference in the context of Heteroge...

Qiming Du, et al. ∙

research

∙ 02/22/2021

Approximation of dilation-based spatial relations to add structural constraints in neural networks

Spatial relations between objects in an image have proved useful for str...

Mateus Riva, et al. ∙

research

∙ 11/02/2020

Tinker-HP : Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields using GPUs and Multi-GPUs systems

We present the extension of the Tinker-HP package (Lagardère et al., Che...

Olivier Adjoua, et al. ∙

research

∙ 04/07/2021

Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering

We introduce an evaluation methodology for visual question answering (VQ...

Corentin Dancette, et al. ∙

research

∙ 07/26/2021

Convergence in quadratic mean of averaged stochastic gradient algorithms without strong convexity nor bounded gradient

Online averaged stochastic gradient algorithms are more and more studied...

Antoine Godichon-Baggioni, et al. ∙

research

∙ 08/02/2021

Neuronal Network Inference and Membrane Potential Model using Multivariate Hawkes Processes

In this work, we propose to catch the complexity of the membrane potenti...

Anna Bonnet, et al. ∙

research

∙ 08/12/2021

Fast Approximation of Persistence Diagrams with Guarantees

This paper presents an algorithm for the efficient approximation of the ...

Jules Vidal, et al. ∙

research

∙ 09/01/2021

Structured Context and High-Coverage Grammar for Conversational Question Answering over Knowledge Graphs

We tackle the problem of weakly-supervised conversational Question Answe...

Pierre Marion, et al. ∙

research

∙ 09/08/2021

Axial multi-layer perceptron architecture for automatic segmentation of choroid plexus in multiple sclerosis

Choroid plexuses (CP) are structures of the ventricles of the brain whic...

Marius Schmidt-Mengin, et al. ∙

research

∙ 09/14/2021

Few-shot Quality-Diversity Optimisation

In the past few years, a considerable amount of research has been dedica...

Achkan Salehi, et al. ∙

research

∙ 10/01/2021

State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting

We present the winning strategy of an electricity demand forecasting com...

Joseph De Vilmarest, et al. ∙

research

∙ 11/02/2021

Discovering and Exploiting Sparse Rewards in a Learned Behavior Space

Learning optimal policies in sparse rewards settings is difficult as the...

Giuseppe Paolo, et al. ∙

research

∙ 12/06/2021

Stable sums to infer high return levels of multivariate rainfall time series

We introduce the stable sums method for inference of extreme return leve...

Gloria Buriticá, et al. ∙

research

∙ 12/06/2021

Learning Connectivity with Graph Convolutional Networks for Skeleton-based Action Recognition

Learning graph convolutional networks (GCNs) is an emerging field which ...

Hichem Sahbi, et al. ∙

research

∙ 12/16/2021

Effective high order integrators for linear Klein-Gordon equations in low to highly oscillatory regimes

We introduce an efficient class of high order schemes for the Klein–Gord...

Karolina Kropielnicka, et al. ∙

research

∙ 12/20/2021

Generalized Pareto Regression Trees for extreme events analysis

In this paper, we provide finite sample results to assess the consistenc...

Sébastien Farkas, et al. ∙

research

∙ 01/14/2022

Uniformly accurate integrators for Klein-Gordon-Schrödinger systems from the classical to non-relativistic limit regime

In this paper we present a novel class of asymptotic consistent exponent...

María Cabrera Calvo, et al. ∙

Sorbonne Université

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