Seminars

APPM Special Seminar - Shilpa Khatri

Feb. 26, 2021

Shilpa Khatri; Health Sciences Research Institute; University of California, Merced Numerical methods for fluid-structure interactions and multiphase flow within marine phenomena To understand the fluid dynamics of marine phenomena, for example particles settling, droplets rising, pulsating coral, and sniffing crabs, fluid-structure and multiphase flow problems must be solved. Challenges exist...

APPM Department Colloquium - Kalesha Bullard

Feb. 26, 2021

Kalesha Bullard, Postdoctoral Researcher, Facebook AI Research Learning through Interaction in Cooperative Multi-Agent Systems Effective communication is an important skill for enabling information exchange and cooperation in multi-agent systems, in which agents coexist in a shared environment with humans and/or other artificial agents. Indeed, human domain experts can be a...

APPM Special Seminar - Olaniyi Iyiola

Feb. 25, 2021

Olaniyi Iyiola, Department of Mathematics and Physical Sciences, California University of Pennsylvania Efficient Methods for Solving Diffusion-Reaction Systems of Fractional Order Type Nonlocality and spatial heterogeneity of many practical systems have made fractional differential equations very useful tools in Science and Engineering. However, solving these type of models is computationally...

Joint APPM/PHYS Colloquium - Philip Stark

Feb. 24, 2021

Philip Stark; Department of Statistics; University of California, Berkeley Evidence-Based Elections Elections rely on people, hardware, and software, all of which are fallible and subject to manipulation. Well resourced nation-states continue to attack U.S. elections. Voting equipment is built by private vendors–some foreign, but all using foreign parts. Many states...

APPM Special Seminar - Eduardo Corona

Feb. 23, 2021

Eduardo Corona, Assistant Professor of Mathematics, New York Institute of Technology Fast computational frameworks for particulate media simulation Granular media and “wet” particle suspensions are two important models of soft matter. They are crucial to the study of soil mechanics, biological media self-assembly and smart material design. In this talk,...

APPM Special Seminar - Yunan Yang

Feb. 22, 2021

Yunan Yang; Courant Instructor; Courant Institute of Mathematical Sciences, New York University Optimal Transport for Inverse Problems and the Implicit Regularization Optimal transport has been one interesting topic of mathematical analysis since Monge (1781). The problem's close connections with differential geometry and kinetic descriptions were discovered within the past century,...

APPM Department Colloquium - Jeffrey Pennington

Feb. 19, 2021

Jeffrey Pennington, Research Scientist, Google Brain Demystifying deep learning through high-dimensional statistics As deep learning continues to amass ever more practical success, its novelty has slowly faded, but a sense of mystery persists and we still lack satisfying explanations for how and why these models perform so well. Among the...

APPM Department Colloquium - Esteban Real

Feb. 12, 2021

Esteban Real, Software Engineer, Google Brain Evolving Machine Learning Algorithms The effort devoted to hand-crafting machine learning (ML) models has motivated the use of automated methods. These methods, collectively known as AutoML, can today optimize the models' architectures to surpass the performance of manual designs. I will discuss how evolutionary...

APPM Department Colloquium - Christian Szegedy

Feb. 5, 2021

Christian Szegedy, Staff Research Scientist, Google Machine Learning for Mathematical Reasoning In this talk I will discuss the application of transformer based language models and graph neural networks on automated reasoning tasks in first-order and higher-order logic. After a short introduction of the type of problems addressed and the general...

APPM Department Colloquium - Rico Sennrich

Jan. 29, 2021

Rico Sennrich, Professor of Computational Linguistics, University of Zurich Lessons from Multilingual Machine Translation Neural models have brought rapid advances to the field of machine translation, and have also opened up new opportunities. One of these is the training of machine translation models in two or more translation directions to...

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