Neural Network & Dynamics
COURSE WEBPAGE: Inferring Structure of Complex Systems https://faculty.washington.edu/kutz/am563/am563.html This lecture introduces the basics of neural ...
Nathan Kutz
Introduction to System Identification
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, you will have a ...
MATLAB
8.6 David Thompson (Part 6): Nonlinear Dimensionality Reduction: KPCA
caltech
Sparse Identification of Nonlinear Dynamics (SINDy)
This video illustrates a new algorithm for the sparse identification of nonlinear dynamics (SINDy). In this work, we combine machine learning, sparse regression, ...
Steve Brunton
Neural Network In 5 Minutes | What Is A Neural Network? | How Neural Networks Work | Simplilearn
This video on "What is a Neural Network" delivers an entertaining and exciting introduction to the concepts of Neural Network. We will learn the different layers ...
Simplilearn
Leaf Recognition Using Convolutional Neural Network by Yuan Liu and Jianing Zhao
Machine Learning 2017 final project: Leaf Recognition Using Convolutional Neural Network by Yuan Liu and Jianing Zhao.
NYU Shanghai Machine Learning 2017
Final Year Project - Optimising Neural Networks for Embedded Systems
My final year project which I completed in 2017 focused on modifying the activation functions in convolutional neural networks to work more efficiently on ...
Robert Koch
Model Predictive Control System | Neural Network | Episode #13
Learn what Model Predictive Control is and how Neural Network is used to design a controller for the plant. We will see how to create an optimization block that ...
MATLAB Helper ®
Two-Level Lattice Neural Network Architectures for Control of Nonlinear Systems - CDC2020
James's talk at the 59th IEEE Conference on Decision and Control for the "Two-Level Lattice Neural Network Architectures for Control of Nonlinear Systems" ...
Resilient Cyber-Physical Systems Lab
Time Series Neural Network GUI | Episode #4
Learn how to use the Graphic User Interface (GUI) for Time Series Neural Network in MATLAB. Learn NN terms such as "Correlation", "Autocorrelation", ...
MATLAB Helper ®
Hybrid system identification and disturbance modeling using neural networks - AIChE 2020 - Pratyush
Pratyush Kumar
Spyros Chatzivasileiadis:From Decision Trees & Neural Networks to MILP for Power System Optimization
How can Neural Networks capture previously intractable constraints (e.g. based on differential equations) in a mixed-integer linear program? Invited to present ...
DTU CEE Lectures: Optimization in Energy Systems
Ising Machines: Non-Von Neumann Computing with Nonlinear Optics - Alireza Marandi - 6/7/2019
Changing Directions & Changing the World: Celebrating the Carver Mead New Adventures Fund. June 7, 2019 in Beckman Institute Auditorium at Caltech.
caltech
Mod-01 Lec-25 Neural Networks for Pattern Recognition (Contd.)
Pattern Recognition and Application by Prof. P.K. Biswas,Department of Electronics & Communication Engineering,IIT Kharagpur.For more details on NPTEL ...
nptelhrd
Data-Driven Dynamical Systems Overview
This video provides a high-level overview of this new series on data-driven dynamical systems. In particular, we explore the various challenges in modern ...
Steve Brunton
Understanding Recurrent Neural Networks Using Response Theory
Speaker: Soon Hoe Lim Event: Second Symposium on Machine Learning and Dynamical Systems http://www.fields.utoronto.ca/activities/20-21/dynamical Title: ...
Fields Institute
Maglev Modeling with Neural Time Series App
Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Model the position of a levitated magnet as ...
MATLAB
MIT 6.S191 (2019): Convolutional Neural Networks
MIT Introduction to Deep Learning 6.S191: Lecture 3 Deep Computer Vision Lecturer: Ava Soleimany January 2019 For all lectures, slides and lab materials: ...
Alexander Amini
Neural Networks in Materials Science
Neural networks are non-linear functions which are extremely flexible and hence can be used to model complex properties. They have many applications in ...
bhadeshia123
Augmenting Differentiable Simulators with Neural Networks to Close the Sim2Real Gap
Our presentation for the R:SS 2020 Workshop on Closing the Reality Gap in Sim2Real Transfer for Robotics Code: ...
Eric Heiden
Lecture 8: Recurrent Neural Networks and Language Models
Lecture 8 covers traditional language models, RNNs, and RNN language models. Also reviewed are important training problems and tricks, RNNs for other ...
Stanford University School of Engineering
13. Speech Recognition with Convolutional Neural Networks in Keras/TensorFlow
Learn to build a Keras model for speech classification. Audio is the field that ignited industry interest in deep learning. Although the data doesn't look like the ...
Weights & Biases
Mod-08 Lec-25 Overview of Artificial Neural Networks
Pattern Recognition by Prof. P.S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore. For more details on NPTEL visit ...
nptelhrd
Introduction - Intelligent Systems Control
Lectures by Prof. Laxmidhar Behera, Department of Electrical Engineering, Indian Institute of Technology, Kanpur. For more details on NPTEL visit ...
nptelhrd
Optimizing neural networks via Koopman operator theory
Speaker: Akshunna S. Dogra Event: Second Symposium on Machine Learning and Dynamical Systems http://www.fields.utoronto.ca/activities/20-21/dynamical ...
Fields Institute
Intro to neural networks
Julia Computing
Using Matlab System Identifcation Toolbox and Simulink to build dynamic models from your market data
http://quantlabs.net/membership.htm.
Bryan Downing
Machine Learning for Fluid Dynamics: Models and Control
This video discusses how machine learning is currently being used to model and control fluid dynamics. Download paper at the Annual Review of Fluid ...
Steve Brunton
Artificial Neural Network Android App
In information technology, a neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural ...
Limitless-X
A mathematical theory of learning in deep neural networks - Surya Ganguli
Surya Ganguli, Stanford University Language, learning, and networks, 12/4/20 https://itsatcuny.org/calendar/language-learning-and-networks.
Initiative for the Theoretical Sciences
Robust Design of Deep Neural Networks Against Adversarial Attacks Based on Lyapunov Theory
Authors: Arash Rahnama, Andre T. Nguyen, Edward Raff Description: Deep neural networks (DNNs) are vulnerable to subtle adversarial perturbations applied ...
ComputerVisionFoundation Videos
2019: Remote sensing precipitation using artificial neural networks and machine learning methods
CUAHSI's 2019 Spring Cyberseminar Series: Recent advances in big data machine learning in Hydrology Date: May 10, 2019 Topic: Remote sensing ...
CUAHSI
Ullrich Köthe | Analyzing Inverse Problems in Natural Science using Invertible Neural Networks
Watch Ullrich Köthe's talk during the First French-German Meeting in Physics, Mathematics and Artificial Intelligence Theory that took place from November 4 to ...
CEA LIST
Module 1 lecture 3 Back Propagation Algorithm revisited
Intelligent Systems Control(M_1_L_3)Lectures by Prof. Laxmidhar Behera, Department of Electrical Engineering, Indian Institute of Technology, Kanpur.
nptelhrd
It's about time. Modelling human visual inference with deep recurrent neural networks.
Tim Kietzmann, Donders Institute for Brain, Cognition and Behaviour.
MITCBMM
Michael Unser: "Splines and imaging: From compressed sensing to deep neural networks"
Deep Learning and Medical Applications 2020 "Splines and imaging: From compressed sensing to deep neural networks" Michael Unser - École Polytechnique ...
Institute for Pure & Applied Mathematics (IPAM)
Session on Convolutional Neural Networks (CNN)
This is the 5th session of the Deep Learning bootcamp designed for intermediate learners. In the session, the speaker talks about the aspects of Convolutional ...
DPhi
Machine learning - Neural networks
Neural Networks Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html Course taught in 2013 at UBC by Nando de Freitas.
Nando de Freitas
Talk: Validation of a Convolutional Neural Network Model for Spike Transformation Using a Generaliz…
Speaker: Bryan Moore, University of Southern California (grid.42505.36) Title: Validation of a Convolutional Neural Network Model for Spike Transformation ...
Neuromatch Conference
Soledad Villar: "Graph neural networks for combinatorial optimization problems"
Machine Learning for Physics and the Physics of Learning 2019 Workshop IV: Using Physical Insights for Machine Learning "Graph neural networks for ...
Institute for Pure & Applied Mathematics (IPAM)
MATLAB Applications - (NAR) Time Series Neural Networks
Taking a look at seasonal data (Sunspots) and creating a function that can be used to predict values in the future. (Recorded with http://screencast-o-matic.com)
Nick Losee
1.06 - Milosovjevic - Solving Astrophysical PDEs with Deep Neural Networks and TensorFlow
Physics in Machine Learning Workshop May 29, 2019 https://bids.berkeley.edu/events/physics-machine-learning-workshop.
Berkeley Institute for Data Science (BIDS)
