Conference on Perspectives in Nonlinear Dynamics #Day 1 (4 of 4)
Conference on Perspectives in Nonlinear Dynamics July 16-19, 2019 Speakers: - Tiago Pereira (ICMC-USP São Carlos, Brazil): Stochastically driven hubs ...
ICTP-SAIFR
Mod-12 Lec-28 Kalman Filter Design -- I
Optimal Control, Guidance and Estimation by Dr. Radhakant Padhi, Department of Aerospace Engineering, IISc Bangalore. For more details on NPTEL visit ...
nptelhrd
Fast Nonlinear Estimation and Control
Fast estimation and control techniques are critical for real-time applications. Researchers at KU Leuven will share cutting-edge methods to apply Nonlinear ...
APMonitor.com
Dr. Yanzhao Cao: "Backward SDE Methods For Nonlinear Filtering Methods"
Presentation by Yanzhao Cao on "Backward SDE Methods For Nonlinear Filtering Methods"" on 11/27/2018 Symposium on “Big Data Challenges for Predictive ...
CICS at Notre Dame
Nonlinear and Stochastic methods in climate and GFD- Takao - Workshop 1 - CEB T3 2019
Takao (Imperial College London) / 07.10.2019 Nonlinear and Stochastic methods in climate and GFD ---------------------------------- Vous pouvez nous rejoindre sur ...
Institut Henri Poincaré
Spatially smooth local ensemble transform particle filtering
Matthew Graham National University of Singapore, Singapore.
Institute for Mathematical Sciences
Data-driven regularisation for solving inverse problems - Carola-Bibiane Schönlieb, Turing/Cambridge
In this talk we discuss the idea of data- driven regularisers for inverse imaging problems. We are in particular interested in the combination of model-based and ...
The Alan Turing Institute
Advancements of the EnKF: inverse problems and optimal transport
Neil Chada National University of Singapore, Singapore.
Institute for Mathematical Sciences
Lecture 22: Stochastic control
Lecture 22: Stochastic control.
Zico Kolter
Stefano Soatto (UCLA): "Dynamics and Control of Differential Learning"
May 30, 2019.
MIT Institute for Data, Systems, and Society
David Duvenaud: Neural Ordinary Equations
Presentation slides can be found here: https://vectorinstitute.ai/wp-content/uploads/2019/03/ode-talk-vector-symposium.pdf Check out the full paper here: ...
Vector Institute
Latent Stochastic Differential Equations | David Duvenaud
A talk from the Toronto Machine Learning Summit: https://torontomachinelearning.com/ The video is hosted by https://towardsdatascience.com/ About the ...
Towards Data Science
The Non-Stochastic Control Problem - Elad Hazan
Computer Science/Discrete Mathematics Seminar I The Non-Stochastic Control Problem Linear dynamical systems are a continuous subclass of reinforcement ...
Institute for Advanced Study
Introduction to Econometrics Toolbox in MATLAB R2008b - Previous Release
See what's new in the latest release of MATLAB and Simulink: https://goo.gl/3MdQK1 Download a trial: https://goo.gl/PSa78r In this webinar, we'll demonstrate ...
MATLAB
Infimal-convolution-type regularization for inverse problems .. - Bredies - Workshop 1 - CEB T1 2019
Bredies (Univ. Graz) / 07.02.2019 Infimal-convolution-type regularization for inverse problems in imaging Infimal-convolution-type regularization for inverse ...
Institut Henri Poincaré
First-Order Stochastic Optimization
Rachel Ward, University of Texas at Austin https://simons.berkeley.edu/talks/clone-intro-his-foundations-data-science-book-ii-1 Foundations of Data Science ...
Simons Institute
Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks
We present an algorithm for policy search in stochastic dynamical systems using model-based reinforcement learning. The system dynamics are described with ...
Microsoft Research
Deep learning for technical computations and equation solving
Adam Andersson, PhD and team leader at Syntronic, presents "Deep learning for technical computations and equation solving" at a meetup hosted by the ...
GAIA
Mod-14 Lec-33 LQG Design; Neighboring Optimal Control & Sufficiency Condition
Optimal Control, Guidance and Estimation by Dr. Radhakant Padhi, Department of Aerospace Engineering, IISc Bangalore. For more details on NPTEL visit ...
nptelhrd
"An Overview of Probabilistic Programming" by Vikash K. Mansinghka
Probabilistic inference is a widely-used, rigorous approach for processing ambiguous information based on models that are uncertain or incomplete. However ...
Strange Loop
Professor Kostas Zygalakis, University of Edinburgh
Bio He received his PhD in computational stochastic differential equations from University of Warwick at 2009 and held postdoctoral positions at the Universities ...
The Alan Turing Institute
DOE CSGF 2011: Turbulence: V&V and UQ Analysis of a Multi-scale complex system
View more information on the DOE CSGF Program at http://www.krellinst.org/csgf. Parviz Moin Center for Turbulence Research Stanford University Turbulent ...
Krell Institute
Kalman Filtering (contd.)
Advanced Process Control by Prof. Sachin C. Patwardhan,Department of Chemical Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.ac.in.
nptelhrd
Stochastic Second Order Optimization Methods II
Fred Roosta, University of Queensland https://simons.berkeley.edu/talks/second-order-methods-ii Foundations of Data Science Boot Camp.
Simons Institute
AAAI 20 / AAAI 2020 Keynotes Turing Award Winners Event / Geoff Hinton, Yann Le Cunn, Yoshua Bengio
Highlighted Topics** 02:52 [Talk: Stacked Capsule Autoencoders by Geoffrey Hinton] 36:04 [Talk: Self-Supervised Learning by Yann LeCun] 1:09:37 [Talk: Deep ...
ICML IJCAI ECAI 2018 Conference Videos
Naiad: a timely dataflow system
Naiad is a distributed system for executing data parallel, cyclic dataflow programs. It offers the high throughput of batch processors, the low latency of stream ...
Association for Computing Machinery (ACM)
Mod-08 Lec-34 Linear Stochastic Dynamics - Kalman Filter Continued.
Dynamic Data Assimilation: an introduction by Prof S. Lakshmivarahan,School of Computer Science,University of Oklahoma.For more details on NPTEL visit ...
nptelhrd
Nexus Trimester - Yue Lu (Harvard University)
Dynamics of Randomized Row-Action Methods for High-Dimensional Estimation Yue Lu (Harvard University) March 11, 2016 Abstract: In this talk, I will present ...
Institut Henri Poincaré
Quantum feedback for measurement and control - L. Martin - PRACQSYS 2018 - CEB T2 2018
Leigh Martin (Quantum Nanoelectronics Laboratory, Department of Physics, University of California, Berkeley, USA & Center for Quantum Coherent Science, ...
Institut Henri Poincaré
Maximum Entropy Models for Texture Synthesis - Leclaire - Workshop 2 - CEB T1 2019
Arthur Leclaire (Univ. Bordeaux) / 14.03.2019 Maximum Entropy Models for Texture Synthesis. The problem of examplar-based texture synthesis consists in ...
Institut Henri Poincaré
Distributed Control of Energy Management Systems
Distributed Control of Energy Management Systems Professor Manfred Morari Automatic Control Laboratory,ETH Zurich Abstract: We will describe two examples ...
CITRIS
Mod-08 Lec-20 Controllability and Observability of linear Time Invariant Systems
Advanced Control System Design by Radhakant Padhi, Department of Aerospace Engineering, IISC Bangalore For more details on NPTEL visit ...
nptelhrd
Toward theoretical understanding of deep learning (Lecture 2) by Sanjeev Arora
DISTINGUISHED LECTURES THREE LECTURES ON MACHINE LEARNING SPEAKER: Sanjeev Arora (Princeton University and Institute for Advanced Study, ...
International Centre for Theoretical Sciences
Lakshmivarahan
PROGRAM: Data Assimilation Research Program Venue: Centre for Applicable Mathematics-TIFR and Indian Institute of Science Dates: 04 - 23 July, 2011 ...
International Centre for Theoretical Sciences
Stochastic Optimal Control in Biology and Engineering
Control under uncertainty is a fundamental problem relevant to biology as well as engineering. Optimality models have explained numerous details of biological ...
UW Video
Nonautonomous and Random Dynamical Systems Into the Climate Sciences - Ghil -Workshop 1 -CEB T3 2019
Ghil (ENS, Paris, and UCLA) / 09.10.2019 Nonautonomous and Random Dynamical Systems Into the Climate Sciences H. Poincaré already raised doubts about ...
Institut Henri Poincaré
Computation in Networks of Neurons in the Brain II
Wolfgang Maass, Technische Universität Graz https://simons.berkeley.edu/talks/maass-computation-ii The Brain and Computation Boot Camp.
Simons Institute
Mad Max: Affine spline insights into deep learning - Richard Baraniuk, Rice University
This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together ...
The Alan Turing Institute
Data Assimilation: variational data assimilation and the ensemble Kalman filter
This presentation was given by Amos Lawless, during the session titled 'Data Assimilation: variational data assimilation and the ensemble Kalman filter'.
European Space Agency, ESA
Joan Bruna "Learning Graph Inverse Problems with Neural Networks"
June 12th, 2018, 12h00-13h00, room Salle Jean Jaurès, 29 rue d'Ulm Joan Bruna (New York University) Title: Learning Graph Inverse Problems with Neural ...
Data science colloquium CFM-ENS
Small noise limits in the stationary regimes by Vivek S Borkar
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ...
International Centre for Theoretical Sciences
Lec-28 Practical Issues in Identification
Lecture Series on Estimation of Signals and Systems by Prof.S. Mukhopadhyay, Department of Electrical Engineering, IIT Kharagpur. For more details on NPTEL ...
nptelhrd
