2019 L'International Gymnix

The 2019 L'International Gymnix competition was the 28th edition of the L'International Gymnix competition. It was held in Montreal, Canada from March 7–10, 2019.

2019 L'International Gymnix
LocationMontreal, Canada
DatesMarch 8-10
Nations7

Medal winners
Event Gold Silver Bronze
Senior
Team  United States
Sloane Blakely
Kara Eaker
Aleah Finnegan
Alyona Shchennikova		  Canada
Haley de Jong
Laurie Denommée
Isabela Onyshko
Emma Spence		  Australia
Romi Brown
Elena Chipizubov
Emma Nedov
Kate Sayer
Individual all-around  Kara Eaker (USA)  Alyona Shchennikova (USA)  Azuki Kokufugata (JPN)
Vault  Aleah Finnegan (USA)  Haley de Jong (CAN) N/A
Uneven Bars  Ana Padurariu (CAN)  Alyona Shchennikova (USA)  Emma Nedov (AUS)
Balance Beam  Kara Eaker (USA)  Sloane Blakely (USA)  Elena Chipizubov (AUS)
Floor Exercise  Azuki Kokufugata (JPN)  Haley de Jong (CAN)  Alyona Shchennikova (USA)
Junior
Team  United States
Skye Blakely
Olivia Greaves
Lillian Lippeatt
Kaylen Morgan		  Belgium
Stacy Bertrandt
Charlotte Beydts
Noémie Louon
Jutta Verkest		  Canada
Zoé Allaire-Bourgie
Rébéka Groulx
Clara Raposo
Rachael Riley
Individual all-around  Zoé Allaire-Bourgie (CAN)  Olivia Greaves (USA)  Skye Blakely (USA)
Vault  Skye Blakely (USA)  Olivia Greaves (USA)  Rachael Riley (CAN)
Uneven Bars  Skye Blakely (USA)  Zoé Allaire-Bourgie (CAN)  Noémie Louon (BEL)
Balance Beam  Noémie Louon (BEL)  Zoé Allaire-Bourgie (CAN)  Lillian Lippeatt (USA)
Floor Exercise  Zoé Allaire-Bourgie (CAN)  Olivia Greaves (USA)  Noémie Louon (BEL)
Challenge
Individual all-around  Violeta Sanchez (ESP)  Katelyn Rosen (USA)  Emily Walker (CAN)
Vault  Audrey Rousseau (CAN)  Kiora Peart-Williams (CAN)  Ilka Juk (CAN)
Uneven Bars  Violeta Sanchez (ESP)
 Erin Modaro (AUS)		 N/A  Jessica Dowling (CAN)
Balance Beam  Laurie-Lou Vézina (CAN)  Emily Lee (USA)  Erin Modaro (AUS)
Floor Exercise  Emily Lee (USA)  Audrey Rousseau (CAN)  Sienna Robinson (USA)

[1][2][3][4]

gollark: The second one is less controversially "yours" than the first.
gollark: Those are different things, though. A face recognition model is going to be trained on a lot of people's faces, and can then generically match faces together. You can then use that to encode someone's face into an embedding vector you can use for matching.
gollark: I had assumed this stuff was now ML-based and so you would just compare embedding vectors or something.
gollark: What are they eigenvectors *of*, exactly?
gollark: eigen is "own" or something, and apparently people prefer that over "characteristic vector/value".

References
  1. "Team Results" (PDF). USA Gymnastics. March 7, 2019.
  2. "Results" (PDF). usagym.org. 2019. Retrieved 2020-03-15.
  3. "Results" (PDF). usagym.org. 2019. Retrieved 2020-03-15.
  4. "Results" (PDF). usagym.org. 2019. Retrieved 2020-03-15.
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