I gave a talk on the workshop on how the synthesis of logic and machine Understanding, Specifically locations such as statistical relational Finding out, can enable interpretability.
Considering synthesizing the semantics of programming languages? We now have a different paper on that, recognized at OOPSLA.
I gave a chat entitled "Perspectives on Explainable AI," at an interdisciplinary workshop focusing on setting up belief in AI.
I attended the SML workshop within the Black Forest, and mentioned the connections among explainable AI and statistical relational Discovering.
Our paper (joint with Amelie Levray) on Studying credal sum-merchandise networks has long been accepted to AKBC. This kind of networks, as well as other kinds of probabilistic circuits, are interesting because they assure that specific forms of likelihood estimation queries is often computed in time linear in the scale of the community.
The post, to look while in the Biochemist, surveys a few of the motivations and strategies for earning AI interpretable and dependable.
Keen on teaching neural networks with sensible constraints? Now we have a new paper that aims towards full satisfaction of Boolean and linear arithmetic constraints on training at AAAI-2022. Congrats to Nick and Rafael!
I gave a seminar on extending the expressiveness of probabilistic relational versions with very first-purchase attributes, including universal quantification over infinite domains.
Url In the last 7 days of October, I gave a talk informally speaking about explainability and ethical obligation in artificial intelligence. Thanks to the organizers for that invitation.
Jonathan’s paper considers a lifted approached to weighted design integration, together with circuit construction. Paulius’ paper develops a measure-theoretic point of view on weighted product counting and proposes a way to encode conditional weights on literals analogously to conditional probabilities, which ends up in major overall performance enhancements.
With the University of Edinburgh, he directs a investigate lab on artificial intelligence, specialising within the unification of logic and equipment Finding out, having a the latest emphasis on explainability and ethics.
The framework is applicable to a large class of formalisms, including probabilistic relational styles. The paper also scientific studies the synthesis problem in that context. Preprint listed here.
Should you be attending AAAI this calendar year, you may be interested in checking out our papers that touch on fairness, abstraction and generalized sum-solution troubles.
Our paper on synthesizing plans with loops in the existence of probabilistic sounds, recognized the journal of approximate reasoning, has also been approved to your ICAPS https://vaishakbelle.com/ journal observe. Preprint to the complete paper listed here.