Statistical Artificial Intelligence and Relational Learning Group is interested in making smart machines that humans can use reliably in their everyday lives. Artificial Intelligence (AI) has made tremendous progress since its early days, and its advancement has helped shape the progress of research in many other fields. Traditionally, AI is used with either the logical approach to address structured problems or with the statistical approach to handle uncertainty. Our research interests lie at the intersection: advancement and application of algorithms that can do both.
Research Highlights
Latest News
01 May 2024 Our paper titled On the Robustness and Reliability of Late Multi-Modal Fusion using Probabilistic Circuits has been accepted to FUSION 2024
Our paper titled “On the Robustness and Reliability of Late Multi-Modal Fusion using Probabilistic Circuits” has been...
26 Apr 2024 Our paper titled Knowledge Intensive Learning of Credal Networks has been accepted to UAI 2024
Our paper titled “Knowledge Intensive Learning of Credal Networks” has been accepted to the 40th Conference on Uncert...
26 Apr 2024 Prof. Natarajan honored with President’s Teaching Excellence Award!
Congratulations to Prof. Sriraam Natarajan on receiving the President’s Teaching Excellence Award for Graduate/Profes...
19 Apr 2024 Our paper titled Building Expressive and Tractable Probabilistic Generative Models: A Review has been accepted to IJCAI 2024 survey track
Our paper titled “Building Expressive and Tractable Probabilistic Generative Models: A Review” has been accepted to t...
16 Apr 2024 Our paper titled Modeling multiple adverse pregnancy outcomes: Learning from diverse data sources has been accepted to AIME 2024
Our paper titled “Modeling multiple adverse pregnancy outcomes: Learning from diverse data sources” has been accepted...
For previous news, see the News Archive
Funding History
2020
2019
2018
2012
Acknowledgements
