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Abstract: With the rise of techlash, an increasing number of users wish they could just say no to data tracking, surveillance capitalism, and the socially divisive effects of creepy technologies in our daily lives. But can we truly walk away from these systems? And what do we learn when we do? In this talk, Vertesi tells […]
A core problem in statistics and machine learning is to approximate difficult-to-compute probability distributions. This problem is especially important in Bayesian statistics, which frames all inference about unknown quantities as a calculation about a conditional distribution. In this talk I review and discuss innovations in variational inference (VI), a method that approximates probability distributions through optimization. VI has been used in myriad applications in machine learning and Bayesian statistics.
Abstract: Existing research on polarization on social media platforms emphasizes the role of algorithmic "filter bubbles" and platform failure in amplifying extreme attitudes among online audiences. This article provides a different approach by focusing on online creators rather than audiences. Christin adapts field theory to examine the dynamics structuring exchanges between social media influencers, which […]
Dr. Peter Lee is Corporate Vice President of Research and Incubations at Microsoft where he leads Microsoft Research and incubates new research-powered products and lines of business in areas such as artificial intelligence, computing foundations, health, and life sciences. He speaks and writes widely on science and technology trends, including the attached NEJM article “Benefits, Limits, […]
How did scientists make sense of data before statistics and computing? This talk will explore this question by focusing on the discovery of vitamins, which occurred in the early 20th century just before the advent of modern statistical methodology. I will describe the varied practices in experimentation and reporting and highlight the sorts of insights required to uncover what "works." Through this discussion, I will draw connections to contemporary data science tools to illustrate their pros and cons in facilitating discovery.
Abstract: Traditionally machine learning has been heavily influenced by neuroscience (hence the name artificial neural networks) and physics (e.g. MCMC, Belief Propagation, and Diffusion based Generative AI). We have recently witnessed that the flow of information has also reversed, with new tools developed in the ML community impacting physics, chemistry and biology. Examples include faster DFT, Force-Field accelerated MD simulations, PDE Neural Surrogate models, generating druglike molecules, and many more. In this talk I will review the exciting opportunities for further cross fertilization between these fields, ranging from faster (classical) DFT calculations and enhanced transition path sampling to traveling waves in artificial neural networks.
ucsd_encore-zoom is inviting you to a scheduled Zoom meeting. Join Zoom Meeting https://ucsd.zoom.us/j/98016992761 Meeting ID: 980 1699 2761 One tap mobile +16699006833,,98016992761# US (San Jose) +12133388477,,98016992761# US (Los Angeles) Dial by your location +1 669 900 6833 US (San Jose) +1 213 338 8477 US (Los Angeles) +1 669 219 2599 US (San Jose) Meeting […]
When Friday, February 21st Where: HDSI MPR 123 Title: The Sound of Data Speaker: Victor Minces Abstract: In this talk, Dr. Minces will give an overview of his career and how it led to the development of Listening to Waves, a program that creates playful activities and web applications that connect music with science through data visualization and sonification. He […]
Jeremy Bernstein MIT CSAIL Monday, March 31 11:00 AM - 12:00 PM (PST) CSE 1242 Title: Metrized Deep Learning Abstract: We build neural networks in a modular and programmatic way using software libraries like PyTorch and JAX. But optimization theory has not caught up to the flexibility of this paradigm, and practical advances in neural net […]
Location: HDSI MPR To watch via zoom please contact: hdsiassistant@ucsd.edu Formerly Incarcerated professor speaking on his lived experience in research. Researchers from Smarr Lab and MOSAIC lab. Noel Vest, PhD, is an Assistant Professor at the Boston University School of Public Health. His research interests include mental health, substance use disorders, and addiction recovery. As […]