10 Oct 2025
Seminar, Lecture, Talk
IAS / School of Science Joint Lecture - Use of Large Animal Models to Investigate Brain Diseases
Abstract Genetically modified animal models have been extensively used to investigate the pathogenesis of age-dependent neurodegenerative diseases, such as Alzheimer (AD), Parkinson (PD), Huntington (HD) diseases, and Amyotrophic Lateral Sclerosis (ALS). The common feature of these diseases…
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2 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - SDE-based deep generative model
Deep generative models are a category of machine learning models that utilizes deep neural networks to model data distributions and generate new samples.
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2 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Data Adaptive Early Stopping in Split LBI: towards Controlling the False Discovery Rate
Early stopping is a widely-used regularization technique to avoid overfitting in iterative algorithms.
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29 Apr 2022
Seminar, Lecture, Talk
Department of Mathematics - Seminar on Statistics - A Learning System in Pandemic Prevention — from macro predictive modeling to small probability estimation
Reproduction number (R
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29 Apr 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Normalizing Flows with Variational Latent Representation
Normalizing flow (NF) has gained popularity over traditional maximum likelihood based methods due to its strong capability to model complex data distributions.
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29 Apr 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Connecting spatial transcriptomics data and single-cell RNA sequencing data using the deep generative model
Spatial transcriptomics (ST) is a groundbreaking method that allows scientists to measure gene activity in a tissue sample and retain spatial information. However, most spatial ST technologies are limited by their resolution.
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29 Apr 2022
Seminar, Lecture, Talk
Department of Mathematics - Seminar on Applied Mathematics - Riemannian Proximal Gradient Methods
In the Euclidean setting, the proximal gradient method and its accelerated variants are a class of efficient algorithms for optimization problems with decomposable objective.
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29 Apr 2022
Seminar, Lecture, Talk
Department of Mathematics - Seminar on PDE - Anisotropic Dynamical Horizons Arising in Gravitational Collapse
Black holes are predicted by Einstein's theory of general relativity, and now we have ample observational evidence for their existence.
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29 Apr 2022
Seminar, Lecture, Talk
OCES Departmental Seminar: Local to Global Drivers of Past and Future Sea-Level and Coastal Environmental Change
Geological proxies provide valuable archives of the sea-level response to past climate variability over periods of more extreme global mean surface temperatures than the brief instrumental period.
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