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Stochastics/Discrete Analysis Seminar: Vadim Gorin, UC Berkeley, TBA
Stochastics/Discrete Analysis Seminar: Vadim Gorin, UC Berkeley, TBA
Speaker's website: https://www.stat.berkeley.edu/~vadicgor/
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Geometry and Topology Seminar: Thomas Weighill, The University of North Carolina at Greensboro, Coarse Embeddings into Hilbert Space for Spaces of Point Clouds
Geometry and Topology Seminar: Thomas Weighill, The University of North Carolina at Greensboro, Coarse Embeddings into Hilbert Space for Spaces of Point Clouds
Given a space X, one may want to know if it can be embedded into a vector space in a controlled way. Interestingly, this question is of interest in both abstract mathematics (for example, it has implications for the Novikov Conjecture) and in data science, where such embeddings are a necessary preprocessing step to traditional…
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Algebra and Combinatorics Seminar: Erik Bates, NC State, A new combinatorial interpretation of the (sum of (generalized)) Fibonacci numbers
Algebra and Combinatorics Seminar: Erik Bates, NC State, A new combinatorial interpretation of the (sum of (generalized)) Fibonacci numbers
The sum of Fibonacci numbers, i.e. the sequence 2, 4, 7, 12, 20, 33, 54, 88, ... has many combinatorial interpretations. For instance, the n-th term in this sequence is the number of length-n binary strings that avoid 001. In this talk, I will describe a related (but to my knowledge, new) interpretation: given a length-3 binary…
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First Year Research Seminar: Yairon Cid-Ruiz and Mohammad Farazmand, NC State, commutative algebra, algebraic geometry and data science, machine learning, modeling
First Year Research Seminar: Yairon Cid-Ruiz and Mohammad Farazmand, NC State, commutative algebra, algebraic geometry and data science, machine learning, modeling
During each 50-minute First Year Research Seminar, two faculty give our new graduate students a short (~20-25 minute), accessible talk about their research or research area. First Year Research Seminar link
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Differential Equations and Nonlinear Analysis Seminar: Stefania Patrizi, The University of Texas at Austin, The Discrete Dislocation Dynamics of Multiple Dislocation Loops
Differential Equations and Nonlinear Analysis Seminar: Stefania Patrizi, The University of Texas at Austin, The Discrete Dislocation Dynamics of Multiple Dislocation Loops
We consider a nonlocal reaction-diffusion equation that physically arises from the classical Peierls–Nabarro model for dislocations in crystalline structures. Our initial configuration corresponds to multiple slip loop dislocations in $\mathbb R^n$, $n\geq 2$. After suitably rescaling the equation with a small phase parameter $\epsilon>0$, the rescaled solution solves a fractional Allen–Cahn equation. We show that,…
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Teaching and Learning Seminar:Megan Ryals, University of Virginia,Integrating Research and Practice: The Development of Technology-Based Learning Activities in Multivariable Calculus
Teaching and Learning Seminar:Megan Ryals, University of Virginia,Integrating Research and Practice: The Development of Technology-Based Learning Activities in Multivariable Calculus
Students often perceive Multivariable Calculus as a collection of disconnected ideas and approach problem solving in the course formulaically. Students need help from instructors in developing spatial reasoning and making connections between symbolic computations and graphical representations. In this talk I will share how I integrated results of research on students’ learning of differential calculus…
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Computational and Applied Mathematics: Anuj Abhishek, Case Western Reserve University, Operator Learning for Inverse Problems
Computational and Applied Mathematics: Anuj Abhishek, Case Western Reserve University, Operator Learning for Inverse Problems
Neural operators such as Deep Operator Networks (DeepONet) and Convolutional Neural Operators (CNO) have been shown to be fairly useful in approximating an operator between two function spaces. In this talk, we will briefly review two inverse problems that arise in Medical Imaging, namely EIT and QPAT. We will also describe the relevant operator learning architectures.…
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Stochastics/Discrete Analysis Seminar: Lechao Xiao, Google DeepMind, Harmonic Analysis and Theory of Deep Learning
Stochastics/Discrete Analysis Seminar: Lechao Xiao, Google DeepMind, Harmonic Analysis and Theory of Deep Learning
The past decade has witnessed a remarkable surge in breakthroughs in artificial intelligence (AI), with the potential to profoundly impact various aspects of our lives. However, the fundamental mathematical principles underlying the success of deep learning, the core technology behind these breakthroughs, is still far from well-understood. In this presentation, I will share some interesting…
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Algebra and Combinatorics Seminar: Luis Ferroni, Institute for Advanced Study, TBA
Algebra and Combinatorics Seminar: Luis Ferroni, Institute for Advanced Study, TBA
Speaker's website: https://sites.google.com/view/ferroniluis
1 event,
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Teaching and Learning Seminar: Eric Hanson, NC State University, TBD
Teaching and Learning Seminar: Eric Hanson, NC State University, TBD
Speaker's Website: https://math.sciences.ncsu.edu/people/ejhanso3/
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Stochastics/Discrete Analysis Seminar: Lê Thái Hoàng, University of Mississippi, TBA
Stochastics/Discrete Analysis Seminar: Lê Thái Hoàng, University of Mississippi, TBA
Speaker's website: https://home.olemiss.edu/~leth/
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2 events,
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Algebra and Combinatorics Seminar: Jack Jeffries, University of Nebraska-Lincoln, TBA
Algebra and Combinatorics Seminar: Jack Jeffries, University of Nebraska-Lincoln, TBA
Speaker's website: https://jack-jeffries.github.io/