Thursday, July 24, 2025

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2025-07-29 / 13:30 ~ 14:30
SAARC 세미나 - SAARC 세미나: 인쇄
by Chung, SueYeon()
Recent breakthroughs in experimental neuroscience and machine learning have opened new frontiers in understanding the computational principles governing neural circuits and artificial neural networks (ANNs). Both biological and artificial systems exhibit an astonishing degree of orchestrated information processing capabilities across multiple scales - from the microscopic responses of individual neurons to the emergent macroscopic phenomena of cognition and task functions. At the mesoscopic scale, the structures of neuron population activities manifest themselves as neural representations. Neural computation can be viewed as a series of transformations of these representations through various processing stages of the brain. The primary focus of my lab's research is to develop theories of neural representations that describe the principles of neural coding and, importantly, capture the complex structure of real data from both biological and artificial systems. In this talk, I will present three related approaches that leverage techniques from statistical physics, machine learning, and geometry to study the multi-scale nature of neural computation. First, I will introduce new statistical mechanical theories that connect geometric structures that arise from neural responses (i.e., neural manifolds) to the efficiency of neural representations in implementing a task. Second, I will employ these theories to analyze how these representations evolve across scales, shaped by the properties of single neurons and the transformations across distinct brain regions. Finally, I will show how these insights extend efficient coding principles beyond early sensory stages, linking representational geometry to efficient task implementations. This framework not only help interpret and compare models of brain data but also offers a principled approach to designing ANN models for higher-level vision. This perspective opens new opportunities for using neuroscience-inspired principles to guide the development of intelligent systems.
2025-07-25 / 14:00 ~ 15:30
학과 세미나/콜로퀴엄 - 위상수학 세미나: 인쇄
by ()
In the 1980s, Thurston introduced a new (asymmetric) metric on Teichmüller space based on best Lipschitz maps between two homeomorphic hyperbolic surfaces, instead of quasi-conformal maps which are used in the original theory of Teichmüller. In this series of lectures, I will explain his theory and discuss recent progress in the field. Three lectures will cover the following topics, but I may also add other materials. (1) General theory of Thurston’s asymmetric metric (2) Geodesics with respect to Thurston’s metric (3) Infinitesimal structures of Teichmüller space with Thurston’s metric
2025-07-25 / 10:00 ~ 11:30
학과 세미나/콜로퀴엄 - 위상수학 세미나: 인쇄
by ()
In the 1980s, Thurston introduced a new (asymmetric) metric on Teichmüller space based on best Lipschitz maps between two homeomorphic hyperbolic surfaces, instead of quasi-conformal maps which are used in the original theory of Teichmüller. In this series of lectures, I will explain his theory and discuss recent progress in the field. Three lectures will cover the following topics, but I may also add other materials. (1) General theory of Thurston’s asymmetric metric (2) Geodesics with respect to Thurston’s metric (3) Infinitesimal structures of Teichmüller space with Thurston’s metric
2025-07-24 / 15:00 ~ 16:30
학과 세미나/콜로퀴엄 - 위상수학 세미나: 인쇄
by ()
In the 1980s, Thurston introduced a new (asymmetric) metric on Teichmüller space based on best Lipschitz maps between two homeomorphic hyperbolic surfaces, instead of quasi-conformal maps which are used in the original theory of Teichmüller. In this series of lectures, I will explain his theory and discuss recent progress in the field. Three lectures will cover the following topics, but I may also add other materials. (1) General theory of Thurston’s asymmetric metric (2) Geodesics with respect to Thurston’s metric (3) Infinitesimal structures of Teichmüller space with Thurston’s metric
2025-07-29 / 16:30 ~ 17:30
IBS-KAIST 세미나 - 이산수학: Merge-width 인쇄
by Colin Geniet(IBS 이산수학 그룹)
This talk is an introduction to the recent notion of merge-width, proposed by Jan Dreier and Szymon Torúnczyk. I will give an overview of the context and motivations for merge-width, namely the first-order model checking problem, and present the definition, some examples, and some basic proof techniques with the example of χ-boundedness. This is based on joint work with Marthe Bonamy.
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