The purpose of this meeting is to raise awareness of machine learning techniques in physics, highlighting pitfalls and best practice through examples. While the organising committe is drawn from the particle physics community we are open to talks from any physics related application.
Unless otherwise specified talks are schedule for 20' with 10' for discussion and there will be a coffee break mid afternoon. We will organise a networking session at the end of the day to continue discussions.
Participants
Adrian Bevan
Denis Derkach
Eric D'Aleo
13:00
→
13:30
Refreshments30m410
410
G. O. Jones Building
Coffee and tea will be available prior to the start of the meeting.
13:30
→
13:40
Introduction10mLG1
LG1
G. O. Jones Building
Set the tone and context of of the meeting.
Speaker:
DrA Bevan(Queen Mary)
13:40
→
14:10
Yandex experience of machine learning in HEP30mLG1
LG1
G. O. Jones Building
Speaker:
DrDenis Derkach(Yandex)
14:10
→
14:40
Experience with Deep Learning at NOvA30mLG1
LG1
G. O. Jones Building
Speaker:
DrJonathan Davies(University of Sussex)
14:40
→
15:10
Generalisation methods30mLG1
LG1
G. O. Jones Building
Speaker:
Tom Stevenson(Queen Mary)
15:10
→
15:40
Coffee Break30m410
410
G. O. Jones Building
15:40
→
16:10
Learning cosmological structure formation with random forests30mLG1
LG1
G. O. Jones Building
Speaker:
Luisa Lucie-Smith(UCL)
16:10
→
16:40
Recent improvements to the Toolkit for Multivariate Analysis (TMVA)30mLG1