January 2022
Abstract: The fields of neuroscience and AI have a long and intertwined history. From the study of simple and complex cells in visual areas of the brain to the recent success of convolution neural networks in many real-world applications, experimental and theoretical neuroscience has contributed significantly to designing smarter machines. In turn, AI models help us better understand brain…
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In this presentation, I will report on the results of my work so far on the concept of intelligence, summarising some of the main points and proposals made, and opening the floor for open discussion about the topic. ***Want to attend one of our events? Sign up here. To get regular updates, subscribe to…
February 2022
Abstract Machine learning models have achieved stunning successes in the IID setting. Yet, beyond this setting, existing models still suffer from two grand challenges: brittle under covariate shift and inefficient for knowledge transfer. In this talk, I will introduce three approaches to tackle these challenges, namely self-supervised learning, causal representation learning, and test-time training. More specifically,…
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Abstract: The world is modular. So – intuitively – it seems clear that cognitive systems that deal with the world should benefit from a modular architecture. Simple or less important problems should use less cognitive resources than complex or important problems, which – intuitively – may be achieved by changing the degree of modularity that a…
April 2022
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May 2022
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June 2022
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July 2022
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October 2022
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