Uploaded October 2023 | Updated September 2026, 2 weeks ago
From Oct. 10-11, 2023, the 5th Annual Industry Showcase brought 30+ ICS industry partners to the UC Irvine campus who were interested in recruiting ICS undergraduate and graduate students for full-time positions and summer internships. For more information, visit https://industryshowcase.ics.uci.edu
Video courtesy of Evan Sevits (ES) Creative Solutions LLC
From Oct. 10-11, 2023, the 5th Annual Industry Showcase brought 30+ ICS industry partners to the UC Irvine campus who were interested in recruiting ICS undergraduate and graduate students for full-time positions and summer internships. For more information, visit https://industryshowcase.ics.uci.edu
Video courtesy of Evan Sevits (ES) Creative Solutions LLC










![AI/ML Seminar Series: Joe Marino (2/1/2021)
UCI AI/ML Seminar Series
https://cml.ics.uci.edu/aiml/
Joe Marino
PhD Student
Computation and Neural Systems
California Institute of Technology
Connecting Variational Autoencoders Back to the Brain
Unsupervised machine learning has recently dramatically improved our ability to model and extract structure from data. One such approach is deep latent variable models, which includes variational autoencoders (VAEs) [Kingma & Welling, 2014; Rezende et al., 2014]. These models can be traced back to the Helmholtz machine [Dayan et al., 1995], which, in turn, was inspired by ideas from theoretical neuroscience [Mumford, 1992]. In the intervening years, neuroscientists have further developed these ideas into a popular theory: predictive coding [Rao & Ballard, 1999; Friston, 2005]. Yet, the machine learning community remains largely unaware of these connections. In this talk, I discuss the links between modern deep latent variable models and predictive coding, yielding several striking implications for the correspondences between machine learning and neuroscience. This motivates a more nuanced view in connecting these fields, including the search for backpropagation in the brain.
Bio:
Joe Marino is a PhD candidate in the Computation & Neural Systems program at Caltech, advised by Yisong Yue. His work focuses on improving probabilistic models and inference techniques, using neuroscience-inspired ideas, within the areas of generative modeling and reinforcement learning. AI/ML Seminar Series: Joe Marino (2/1/2021)](https://i.ytimg.com/vi/iVz6uwD7i6A/mqdefault.jpg)