activity
20182021
most citedFully Parallel Hyperparameter Search: Reshaped Space-Filling

11 citations · 11 across the 1 of their papers we have counts for

collaborators

5 papers

cs.SD2021

Multimodal Self-Supervised Learning of General Audio Representations

Luyu Wang, Pauline Luc, Adria Recasens +2

We present a multimodal framework to learn general audio representations from videos. Existing contrastive audio representation learning methods mainly focus on using the audio mod…

cs.CV2021

Broaden Your Views for Self-Supervised Video Learning

Adrià Recasens, Pauline Luc, Jean-Baptiste Alayrac +11

Most successful self-supervised learning methods are trained to align the representations of two independent views from the data. State-of-the-art methods in video are inspired by…

cs.AI2020

Game Plan: What AI can do for Football, and What Football can do for AI

Karl Tuyls, Shayegan Omidshafiei, Paul Muller +33

The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individual sports, including baseball,…

cs.LG201911 cited

Fully Parallel Hyperparameter Search: Reshaped Space-Filling

M. -L. Cauwet, C. Couprie, J. Dehos +5

Space-filling designs such as scrambled-Hammersley, Latin Hypercube Sampling and Jittered Sampling have been proposed for fully parallel hyperparameter search, and were shown to be…

cs.CV2018

Predicting Future Instance Segmentation by Forecasting Convolutional Features

Pauline Luc, Camille Couprie, Yann LeCun +1

Anticipating future events is an important prerequisite towards intelligent behavior. Video forecasting has been studied as a proxy task towards this goal. Recent work has shown th…