Loss functions and constraints improve sea surface height prediction

In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...
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Linear regression using gradient descent explained simply

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...
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Mini-batch gradient descent in deep learning explained

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...
IEEE

Gradient Descent for Unbounded Convex Functions on Hadamard Manifolds and its Applications to Scaling Problems

Abstract: In this paper, we study asymptotic behaviors of continuous-time and discrete-time gradient flows of a “lower-unbounded” convex function on a Hadamard manifold, particularly, their ...
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What Are The Torque Tubes On Corvettes For?

From a scientific perspective, getting a car moving from Point A to Point B is all about physics and energy transfer. How do you turn the up and down reciprocating motion of an engine's pistons into ...
IEEE

Learning to Explain: a Gradient-based Attribution Method for Interpreting Super-Resolution Networks

Abstract: DNN-based super-resolution(SR) models inherit the black-box nature of DNN and present low transparency. However, few works focus on interpreting low-level SR models and the limited existing ...