
Designing a NISQ Reservoir with Maximal Memory Capacity for Volatility Forecasting
28 Oct 2020   Contributor(s):: Samudra Dasgupta
In this talk, we lay out the systematic design considerations for using a NISQ reservoir as a computing engine. We then show how to experimentally evaluate the memory capacity of various reservoir topologies (using IBMQ’s Rochester device) to identify the configuration with maximum...

Samudra Dasgupta
Samudra Dasgupta obtained his B.Tech in Electronics and Electrical Engineering from IITKharagpur 2006, followed by M.S. in Engineering and Applied Sciences from Harvard 2008 and an M.B.A. from...
https://nanohub.org/members/305162

Interactive Learning Tools for Scientific Computing and Data Analysis Using R
29 Jul 2020   Contributor(s):: Cindy Nguyen, Rei SanchezArias
Rootfinding methods and numerical optimization techniques with applications in science, engineering, and data analysis

ECE 595ML Lecture 1.2: Linear Regression  Geometry
28 May 2020   Contributor(s):: Stanley H. Chan

PennyLane  Automatic Differentiation and Machine Learning of Quantum Computations
29 Apr 2020   Contributor(s):: Nathan Killoran
PennyLane is a Pythonbased software framework for optimization and machine learning of quantum and hybrid quantumclassical computations.

Advances in Computational and Quantum Imaging Workshop
28 Jan 2020 
The purpose of the workshop is to bring different communities together, review recent theoretical and experimental advances and explore synergetic collaborations. The workshop aligns well with the significant investments in quantum technologies through the National Quantum Initiative in the...

ECE 595ML Lecture 1.1: Linear Regression
21 Jan 2020   Contributor(s):: Stanley H. Chan

ECE 595ML Lecture 2.1: Regularized Linear Regression
21 Jan 2020   Contributor(s):: Stanley H. Chan

ECE 595ML: Machine Learning I
17 Jan 2020   Contributor(s):: Stanley H. Chan
Spring 2020  This course is in productionCourse Website: https://engineering.purdue.edu/ChanGroup/ECE595/index.htmlCourse Outline:Part 1: Mathematical BackgroundLinear Regression and OptimizationPart 2: ClassificationMethods to train linear classifiersFeature analysis, Geometry, Bayesian...

Universal Variational Quantum Computation
28 Oct 2019   Contributor(s):: Jacob Biamonte
We show that the variational approach to quantum enhanced algorithms admits a universal model of quantum computation.

Quantum Algorithmic Breakeven: on Scaling Up with Noisy Qubits
21 Aug 2019   Contributor(s):: Daniel Lidar
In this talk I will argue in favor of a different criterion I call "quantum algorithmic breakeven," which focuses on demonstrating an algorithmic scaling improvement in an errorcorrected setting over the uncorrected setting. I will present evidence that current experiments with...

Overview of Computational Methods and Machine Learning: Panel Discussion
14 Jun 2019   Contributor(s):: Brett Matthew Savoie, Pradeep Kumar Gurunathan, Peilin Liao, Xiulin Ruan, Guang Lin
The individual Panel Talks which accompanies this discussion can be found here.Why do we need experiments?Are your methods “descriptive” or “predictive”?Do you work with any other theory/simulation groups?On the 5 year timescale: is machinelearning hype or a real...

Overview of Computational Methods and Machine Learning: Panel Talks
14 Jun 2019   Contributor(s):: Brett Matthew Savoie, Pradeep Kumar Gurunathan, Peilin Liao, Xiulin Ruan, Guang Lin
The Panel Discussion which follows these individual presentations can be found here.Individucal Presentations:Theory and Machine Learning in the Chemical Sciences, Brett Matthew Savoie;Divide and Conquer with QM/MM Methods, Pradeep Kumar Gurunathan;Computational Chemistry/Materials, Peilin...

Big Data in Reliability and Security: Some Basics
30 May 2019   Contributor(s):: Saurabh Bagchi

Big Data in Reliability and Security: Applications
30 May 2019   Contributor(s):: Saurabh Bagchi

Peter Shor
Peter Shor is Morss Professor of Applied Mathematics since 2003, and Chair of the Applied Mathematics Committee since 2015. He received the B.A. in mathematics from Caltech in 1981, and the Ph.D....
https://nanohub.org/members/230531

HumanInterpretable Concept Learning via Information Lattices
23 May 2019   Contributor(s):: Lav R. Varshney
The basic idea is an iterative discovery algorithm that has a studentteacher architecture and that operates on a generalization of Shannon’s information lattice, which itself encodes a hierarchy of abstractions and is algorithmically constructed from grouptheoretic foundations.

Janet Daetton
Janet Daetton is a teacher and private tutor working at school for 8 years. She has an educational blog with tips for students and lifelong learners. Her first business experience is being an...
https://nanohub.org/members/228343

Feb 25 2019
Software Productivity and Sustainability for CSE and Data Science
The SIAM CSE conference seeks to enable indepth technical discussions on a wide variety of major computational efforts on largescale problems in science and engineering, foster the...
https://nanohub.org/events/details/1738

Networked Dynamical Systems for Function and Learning: Paradigms for DataDriven Control and Learning in Neurosensory Systems
16 Jan 2019   Contributor(s):: J. Nathan Kutz
Our objective is to use emerging datadriven methods to extract the underlying engineering principles of cognitive capability, namely those that allow complex networks to learn and enact control and functionality in the robust manner observed in neurosensory systems. Mathematically, the...