Main

related bits

0

processing priority

3

site type

0 (generic, awaiting analysis)

review version

11

html import

20 (imported)

Events

first seen date

2024-11-05 15:16:01

expired found date

-

created at

2024-11-05 15:16:01

updated at

2024-11-05 15:16:02

Domain name statistics

length

13

crc

46690

tld

86

nm parts

0

nm random digits

0

nm rare letters

0

Connections

is subdomain of id

87719371 (github.io)

previous id

0

replaced with id

0

related id

-

dns primary id

0

dns alternative id

0

lifecycle status

0 (unclassified, or currently active)

Subdomains and pages

deleted subdomains

0

page imported products

0

page imported random

0

page imported parking

0

Error counters

count skipped due to recent timeouts on the same server IP

0

count content received but rejected due to 11-799

0

count dns errors

0

count cert errors

0

count timeouts

0

count http 429

0

count http 404

0

count http 403

0

count http 5xx

0

next operation date

-

Server

server bits

server ip

-

Mainpage statistics

mp import status

20

mp rejected date

-

mp saved date

-

mp size orig

8472

mp size raw text

3234

mp inner links count

3

mp inner links status

10 (links queued, awaiting import)

Open Graph

title

description

image

site name

author

updated

2026-02-20 14:58:49

raw text

Quentin BERTRAND - Home Quentin BERTRAND - Home Since July 1st, I am a researcher (‘chargé de recherche‘) at Inria Lyon and Université Jean Monnet , in the Malice team , located in Laboratoire Hubert Curien . I work on optimization, games, and representation learning. From November 2021 to June 2024, I was a post-doctoral researcher at Mila working with Gauthier Gidel and Simon Lacoste-Julien . Prior to this position, I did my Ph. D. at Inria Paris-Saclay (in the Parietal Team ) under the supervision of Joseph Salmon and Alexandre Gramfort . I worked on the optimization and statistical aspects of high dimensional sparse linear regression applied to brain signal reconstruction. In particular, Our recent works on self-consuming generative models and their biases got media coverage from the N.Y. times ! I developed Python packages for fast computation and automatic hyperparameter selection of sparse linear models. Here is a short resume and my list ...

Text analysis

redirect type

0 (-)

block type

0 (no issues)

detected language

1 (English)

category id

AI [en] (229)

index version

2025123101

spam phrases

0

Text statistics

text nonlatin

0

text cyrillic

0

text characters

2534

text words

484

text unique words

227

text lines

98

text sentences

22

text paragraphs

12

text words per sentence

22

text matched phrases

2

text matched dictionaries

2

RSS

rss path

rss status

1 (priority 1 already searched, no matches found)

rss found date

-

rss size orig

0

rss items

0

rss spam phrases

0

rss detected language

0 (awaiting analysis)

inbefore feed id

-

inbefore status

0 (new)

Sitemap

sitemap path

sitemap status

1 (priority 1 already searched, no matches found)

sitemap review version

2

sitemap urls count

0

sitemap urls adult

0

sitemap filtered products

0

sitemap filtered videos

0

sitemap found date

-

sitemap process date

-

sitemap first import date

-

sitemap last import date

-