Simon Fraser University

Finite Difference Approximations of Derivatives

First-order derivatives: n additional function calls are needed. Second-order derivatives based on gradient calls, when the "grd" module is specified (Dennis and Schnabel 1983): n additional gradient ...
Nature

Thirty years of Alzheimer's disease genetics: the implications of systematic meta-analyses

Alzheimer's disease (AD) is a highly heritable disorder, the genetic underpinnings of which remain incompletely understood despite intense research over the past 30 years. Over 1,000 individual ...
Investopedia

What is a Back-Of-The-Envelope Calculation? Quick Math Estimation Guide

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...
Investopedia

Understanding the Least Squares Criterion for Accurate Data Fitting

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...
IEEE

A Numerical Approximation Approach for Deriving Computational Efficient Inverse Dynamics of 6-DOF Parallel Robots Based on Principle of Virtual Work

Abstract: The inverse dynamics of the six degree-of-freedom (6-DOF) parallel robot (PR) presents an inherent complexity due to the closed-loop kinematic chains. To derive computational efficient ...
IEEE

Accelerated Successive Convex Approximation for Nonlinear Optimization-Based Control

Abstract: The successive convex approximation (SCA) methods stand out as the viable option for nonlinear optimization-based control, as it effectively addresses the challenges posed by nonlinear ...
IEEE

Approximation-Aware Training for Efficient Neural Network Inference on MRAM Based CiM Architecture

Abstract: Convolutional neural networks (CNNs), despite their broad applications, are constrained by high computational and memory requirements. Existing compression techniques often neglect ...
IEEE

Efficient Algorithm of Contraction High-Order Born Approximation on LWD Ultra-Deep Resistivity Measurement in 3-D Anisotropic Formation

Abstract: With the development of computation methods and the requirement of data processing, it is often required to execute electromagnetic (EM) simulations in a lot of different complex formation ...
IEEE

A Fully Probabilistic Model for Sigmoid Approximation and Its Hardware- Efficient Implementation

Abstract: The sigmoid function is a representative activation function in shallow neural networks. Its hardware realization is challenging due to the complex exponential and reciprocal operations.
IEEE

Towards Exascale Simulations of Nanoelectronic Devices in the GW Approximation

Abstract: Experimental development of gate-all-around silicon nanowire field-effect transistors (NWFETs), a viable replacement for FinFETs, can be complemented by technology computer-aided design.
IEEE

Exploring Approximation and Dataflow Co-Optimization for Scalable Transformer Inference Architecture on the Edge

Abstract: Transformer-based neural networks (NNs) prevail in today’s artificial intelligence applications, including autonomous driving, natural language processing and generative modeling, showing ...