4 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Unified Gas-kinetic methods for multi-scale flow
Multi-scale methods are constantly demanded for scientific research and industry application. This report reviews family of unified gas-kinetic methods for modeling multi-scale flows.
4 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Feature Flow Regularization: Improving Structured Sparsity in Deep Neural Networks
Pruning is a model compression method that removes redundant parameters and accelerates the inference speed of deep neural networks while maintaining accuracy. Most available pruning methods impose various conditions on parameters or features directly.
4 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Provable Tensor-Train Format Tensor Completion by Riemannian Optimization
The tensor train (TT) format enjoys appealing advantages in handling structural high-order tensors. The recent decade has witnessed the wide applications of TT-format tensors from diverse disciplines, among which tensor completion has drawn considerable attention.
4 May 2022
Seminar, Lecture, Talk
Physics Department - Condensed Matter Seminar: What is “Qiu Ku” and How to Measure Quantum Entanglement with It
4 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Integration of single-cell atlases with generative adversarial networks
As single-cell technologies evolved over years, diverse single-cell atlas datasets have been rapidly accumulated. Integrative analyses harmonizing such datasets provide opportunities for gaining deep biological insights.
4 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Highest weight crystals for Schur Q-functions
In 1990s, Kashiwara and Lusztig defined crystals as abstraction of crystal bases of quantum group representations.
3 May 2022
Seminar, Lecture, Talk
Department of Mathematics - PhD Student Seminar - Apply threshold dynamics algorithm to minimal compliance problem in topology optimization
Inspired by the simple two-step threshold dynamics algorithm which iteratively does convolution and thresholding to simulate the motion of grain boundaries, we developed an algorithm to approach the minimal compliance problem in topology optimization with
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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