Lectures


Lecture 1: Deep Learning in Science 1/3

Abstract: TBA

Lecture 2: Deep Learning in Science 2/3

Abstract: TBA

Lecture 3: Deep Learning in Science 3/3

Abstract: TBA



Lecture 1: TBA

Abstract: TBA

Lecture 2: TBA

Abstract: TBA

Lecture 3: TBA

Abstract: TBA



Lecture 1: TBA

Abstract: TBA

Lecture 2: TBA

Abstract: TBA



Lecture 1: TBA

Abstract: TBA

Lecture 1: TBA

Abstract: TBA



Lecture 1: TBA

Abstract: TBA

Lecture 2: TBA

Abstract: TBA



Lecture 1: Knowledge Processing, Logic, and the Future of AI (1/2)

Nowadays, when people speak about AI, they usually mean machine learning. Machine learning, in particular, deep learning, is a  powerful method for generating a type of knowledge that could be classified as self-learned knowledge. We humans, on the other hand, make heavy use of two types of knowledge: (i) self-learned knowledge and (ii) transferable knowledge learned or generated by others. If you read this and/or attend the talk, this is  mainly because of this second type of Knowledge. In this talk, I will argue that the combination of both types of knowledge is needed for more powerful and fair automated decision making or decision support,  and thus for the next level of AI. I will discuss various requirements for reasoning formalisms towards this purpose.  After discussing logical languages for knowledge-representation and reasoning, I will briefly  introduce the VADALOG  system developed at Oxford and give an outlook on my recent project RAISON DATA funded by the Royal Society.

Lecture 2: Knowledge Processing, Logic, and the Future of AI (2/2)

Nowadays, when people speak about AI, they usually mean machine learning. Machine learning, in particular, deep learning, is a  powerful method for generating a type of knowledge that could be classified as self-learned knowledge. We humans, on the other hand, make heavy use of two types of knowledge: (i) self-learned knowledge and (ii) transferable knowledge learned or generated by others. If you read this and/or attend the talk, this is  mainly because of this second type of Knowledge. In this talk, I will argue that the combination of both types of knowledge is needed for more powerful and fair automated decision making or decision support,  and thus for the next level of AI. I will discuss various requirements for reasoning formalisms towards this purpose.  After discussing logical languages for knowledge-representation and reasoning, I will briefly  introduce the VADALOG  system developed at Oxford and give an outlook on my recent project RAISON DATA funded by the Royal Society.



Lecture 1: TBA

Abstract: TBA

Lecture 2: TBA

Abstract: TBA



Lecture 1: TBA

Abstract: TBA

Lecture 2: TBA

Abstract: TBA

Lecture 3: TBA

Abstract: TBA



Lecture 1: TBC
Lecture 2: TBC
Lecture 3: TBC


Lecture: TBA

Abstract: TBA



Lecture 1: TBA

Abstract: TBA

Lecture 2: TBA

Abstract: TBA

Lecture 3: TBA

Abstract: TBA



Lecture 1: TBA

Abstract: TBA

Lecture 2: TBA

Abstract: TBA

Lecture 3: TBA

Abstract: TBA