| Title | : | Measuring and Improving the Internal Conceptual Representations of Deep Learning |
| Speaker | : | Dr. Ramakrishna Vedantam (Visiting researcher at the New York University (NYU) center for data science (CDS)) |
| Details | : | Thu, 20 Apr, 2023 10:00 AM @ CS25 |
| Abstract: | : | Endowing machines with abstract, flexible conceptual representations and the ability to combine known concepts to make novel, “conceptual-leaps†is a long-standing goal of artificial intelligence (AI). In pursuit of this goal, I will discuss my works on the foundations of concept learning for deep learning models. In particular I will focus on: multimodal learning (to ground concept representations more precisely into the world), quantifying robustness (to assess if atomic concepts are learnt correctly) and machine reasoning (to combine known atomic concepts into novel, emergent ones). Finally, I will speculate on important research directions to pursue for realizing the promise of general, robust and human interpretable AI systems. |
