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Panel Presentation: Liquid Neural Networks with Live Q&A

Presented By: Mathias Lechner, PhD & Ramin Hasani, PhD Webinar: Panel Presentation: Liquid Neural Networks with Live Q&A Webinar Abstract: In this talk, we will discuss the nuts and bolts of the novel continuous-time neural network models: Liquid Time-Constant Networks (LTCs). Liquid neural networks are nonlinear state-space models with an input-dependent varying (i.e., liquid) time characteristic. Their outputs are computed by numerical differential equation (DE) solvers when described by ordinary DEs, and by continuous functions when described in closed-form. Liquid networks exhibit stable, bounded and dynamic causal behavior, yield superior expressivity within the family of CT neural models, and give rise to improved performance on a wide range of time series prediction tasks In and out of distribution compared to advanced recurrent models. Earn PACE Credits: 1. Make sure you’re a registered member of Labroots (https://www.labroots.com/ms/webinar/p...) 2. Watch the webinar on YouTube or on the Labroots Website (https://www.labroots.com/ms/webinar/p...) 3. Click Here to get your PACE credits (Expiration date – March 08, 2025): (https://www.labroots.com/credit/pace-...) Labroots on Social: Facebook:   / labrootsinc   Twitter:   / labroots   LinkedIn:   / labroots   Instagram:   / labrootsinc   Pinterest:   / labroots   SnapChat: labroots_inc