Dejan Slepcev (CMU) -- Variational problems on random structures Published 2018-09-18 Download video MP4 360p Download video MP4 720p Recommendations 1:05:39 RI Seminar: Michael Kaess: Factor Graphs for Robot Perception 03:50 The Most Beautiful Equation in Math 1:09:13 Lecture 1 | The Perceptron - History, Discovery, and Theory 26:11 Street Fighting Mathematics || @ CMU || Lecture 1c of TCS Toolkit 58:47 Umbra: A Disk-Based System with In-Memory Performance (Thomas Neumann) 27:22 2023 CCSP Workshop - Frederic Koehler (Stanford) 1:54:37 2023 CCSP Workshop - Tutorial - Kuikui Liu (MIT) 1:21:55 Lecture 1.1: Introduction (Multimodal Machine Learning, Carnegie Mellon University) 1:03:59 Lecture 01: Course Overview (CMU 15-462/662) 1:02:52 RI Seminar: Russ Tedrake : Motion Planning Around Obstacles with Graphs of Convex Sets 1:18:43 Lecture 3 | Learning, Empirical Risk Minimization, and Optimization 35:51 How to do CS Theory || @ CMU || Lecture 1b of CS Theory Toolkit 1:10:26 RI Seminar: Stefan Schaal : From Movement Primitives to Associative Skill Memories 59:06 RI Seminar: Yong-Lae Park : Bio-Inspired Soft Robotics: New Ways of Sensing and Actuation 1:55:28 2023 CCSP Workshop - Tutorial - Will Perkins (Georgia Tech) 1:54:36 Lecture 1. Introduction and Basics - Carnegie Mellon - Computer Architecture 2015 - Onur Mutlu 1:08:48 10^500 Parallel Universes: Lecture 1 of Quantum Computation and Information at CMU 17:50 2024's Game-Changing Robots (What Can They Do?) 1:57:31 2023 CCSP Workshop - Tutorial - Virginia Vassilevska Williams (MIT) 1:17:01 Lecture 4 | The Backpropagation Algorithm Similar videos 1:10:05 PDE on Graphs and Their Continuum Limits 59:13 1W-MINDS: John Harlim, December 2, Diffusion maps on manifolds with boundaries for solving PDEs 46:00 OWOS: Antonin Chambolle - "Derivatives of Solutions of Saddle-Point Problems" 59:26 Mathematical Imaging: From Geometric PDEs and Variational Modeling to Deep Learning for Images 1:03:36 PLATEAU PROBLEM: OLD AND NEW RESULTS - GUIDO DE PHILIPPIS 51:37 Jeff Calder - Random walks and PDEs in graph-based learning 1:09:09 Accelerated Optimization in the PDE Framework 1:03:36 Poisson learning: Graph-based semi-supervised learning at very low label rates, Jeff Calder@UofM 51:54 Moritz Hardt (UC Berkeley) -- When Recurrent Models Don't Need To Be Recurrent 51:07 CMU - 36-705 - 2016-09-26 37:06 Nonlocal Wasserstein Distance and the Associated Gradient Flows 45:52 Nicolás García Trillos - Regularity theory and uniform convergence of graph Laplacian eigenvectors 01:17 Image Segmentation | Mumford-Shah | Calculus of Variations | Ambrosio-Tortorelli Approx| PDE| python 1:20:17 Lecture 16 | Computer Vision 1:06:08 test 41:54 Erwin Topp (USACH, Chile) - Some results on periodic homogenization for fractional Hamilton-Jacobi.. 1:04:11 IMA Workshop:Optimal Control, Optimal Transport, and Data Science 01:06 How To Pronounce Gordana🌈🌈🌈🌈🌈🌈Pronunciation Of Gordana 1:05:54 #22: Robert Young - Metric differentiation and Lipschitz embeddings in Lp paces More results