is seeking a PhD candidate in causality-inspired machine
learning (ML), i.e. the application of ideas from causality to different
areas of ML, under the supervision of Dr Sara Magliacane (
smaglia.wordpress.com). In particular, we are looking for PhD students that
are interested in exploring the connections
10, 2021
- Submission of revised manuscript: January 21, 2022
- Notification of final decision: February 18, 2022
** Guest Editors **
- Kun Zhang (Carnegie Mellon University)
- Ilya Shpitser (Johns Hopkins University)
- Sara Magliacane (University of Amsterdam, MIT-IBM Watson AI Lab
here *on July 30th*!
More information on the workshop and submissions can be found at:
https://sites.google.com/uw.edu/causaluai2021
On behalf of the organizers,
Ema Perković (chair), University of Washington
Frederick Eberhardt, Caltech
Sara Magliacane, University of Amsterdam / MIT-IBM Wat
of first review: December 10, 2021
- Submission of revised manuscript: January 21, 2022
- Notification of final decision: February 18, 2022
** Guest Editors **
- Kun Zhang (Carnegie Mellon University)
- Ilya Shpitser (Johns Hopkins University)
- Sara Magliacane (University of Amsterdam, MIT-IBM
theory and methods for extracting and fusing
causal knowledge from multiple modalities. INDElab has both expertise in
causality as well as in data integration and extraction from multimodal
data. In the lab, you will be working closely with Dr. Sara Magliacane and
Prof. Paul Groth on this project
known%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C=xYP8AvZ1VI3f6iXuwBC5J%2Fd3rID8%2FEntttnHBuMpCH0%3D=0
CRL
***ORGANIZERS***
Sara Magliacane, University of Amsterdam and MIT-IBM Watson AI Lab
Atalanti Mastakouri, Amazon
Yuki Asano, University of Amsterdam and Qualcomm Res
his
into account. The workshop will not have proceedings, so you can submit
recent work or work in progress.
Submission site:
https://openreview.net/group?id=auai.org/UAI/2022/Workshop/CRL
***ORGANIZERS***
Julius von Kügelgen, MPI & University of Cambridge
Luigi Gresele, MPI
Francesco
*Reminder: *10 days to submission deadline (Oct 28 11:59pm AoE)
We invite submissions to the *2nd Conference on Causal Learning and
Reasoning* (CLeaR 2023, https://www.cclear.cc/2023), and welcome paper
submissions that describe new theory, methodology, and/or applications
relevant to any aspect
College London)
Biwei Huang (UCSD)
Atalanti Mastakouri (Amazon)
Joris Mooij (University of Amsterdam)
Cristopher Salvi (Imperial College London)
Organizers
Sören Becker (Helmholtz AI)
Alexis Bellot (DeepMind)
Cecilia Casolo (Helmholtz AI)
Niki Kilbertus (TU Munich, Helmholtz AI)
Sara
Call for Papers
We invite submissions to the *2nd Conference on Causal Learning and
Reasoning* (CLeaR 2023, https://www.cclear.cc/2023), and welcome paper
submissions that describe new theory, methodology, and/or applications
relevant to any aspect of causal learning and reasoning in the fields
testing them empirically?
The Intelligent Data Engineering Lab at the University of Amsterdam (
www.uva.nl) is seeking a motivated PhD student in the area of causality,
causal representation learning and multimodal data fusion. You will be
working under the supervision of dr. Sara Magliacane (
https
We invite you to participate in the *2nd Conference on Causal Learning and
Reasoning* (CLeaR 2023,
of this project is
to leverage causality-inspired machine learning methods to improve the
robustness of fraud detection methods to distribution shifts. This position
will be supervised by dr. Sara Magliacane
<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsaramagliacane.github.io%2F=05%7
known%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C=PwN5s3moWLjpdu22L7xzYbFCaWNMT3R3IK8wqcUZP18%3D=0
***ORGANIZERS***
Sara Magliacane, University of Amsterdam and MIT-IBM Watson AI Lab
Atalanti Mastakouri, Amazon
Yuki Asano, University of Amsterdam and Qualcomm Research
Claudia Shi, Col
causal
drivers of user behaviour through reusing existing A/B test results and
designing new sample efficient experiments. This position will be
supervised by dr. Sara Magliacane
(https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsaramagliacane.github.io%2F=05%7C02%7Cuai
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