Speakers have been asked to recommend reading material relevant for their talks. Participants are highly recommended to familiarise themselves with these items, before the meeting.
LARRY WASSERMAN:
1. "Global and Local Two-Sample Tests via Regression", llmun Kim, Ann B. Lee, Jing Lei, https://arxiv.org/abs/1812.08927
2. Classification accuracy as a proxy for two-sample testing, Ilmun Kim, Aaditya Ramdas, Aarti Singh, Larry Wasserman
https://projecteuclid.org/journals/annals-of-statistics/volume-49/issue-1/Classification-accuracy-as-a-proxy-for-two-sample-testing/10.1214/20-AOS1962.short
3. "Model-Independent Detection of New Physics Signals Using Interpretable Semi-Supervised Classifier Tests",
Purvasha Chakravarti, Mikael Kuusela, Jing Lei, Larry Wasserman. https://arxiv.org/abs/2102.07679
4. "Detecting new signals under background mismodelling", Sara Algeri, https://arxiv.org/abs/1906.06615
BEN NACHMAN:
"Machine Learning in the Search for New Fundamental Physics", https://arxiv.org/abs/2112.03769 .
INES OCHOA
1. The actual ATLAS dijet paper: "Dijet resonance search with weak supervision using √s=13 TeV pp collisions in the ATLAS detector”, https://arxiv.org/abs/2005.02983
2. "Classification without labels: Learning from mixed samples in high energy physics”, https://arxiv.org/abs/1708.02949
GREGOR KASCIECZKA:
"The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics", https://arxiv.org/abs/2101.08320 .
SASCHA CARON:
1. " The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider", https://inspirehep.net/literature/1866115 .
2. "Rare and Different: Anomaly Scores from a combination of likelihood and out-of-distribution models to detect new physics at the LHC", https://inspirehep.net/literature/1869277
ANDREA WULZER:
Link to recording of Andrea's Seminar at CERN on "Leaning New Physics from a Machine", https://indico.cern.ch/event/1097495/ . The most recent corresponding article is at https://inspirehep.net/literature/1977309 .
