PDE-Net: Learning PDEs from Data
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Updated
Jun 26, 2021
PDE-Net: Learning PDEs from Data
Labs for the Foundations of Applied Mathematics curriculum.
pyHarmonySearch is a pure Python implementation of the harmony search (HS) global optimization algorithm.
Python for Random Matrix Theory: cleaning schemes for noisy correlation matrices.
Study notes for my state examination in Sofia University
PowerShell “standard” library for supercharging your productivity. Provides a powerful cross-platform scripting environment enabling efficient analysis and sustainable science in myriad contexts.
A pyTorch Extension for Applied Mathematics
Introduction to Applied Mathematics and Informatics in Drug Discovery (AMIDD)
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
Applied Mathematical Methods in Materials Engineering
Reinforcement Learning based 'Learning' of Dynamic Sepsis Treatment Strategies
A statistical decomposition of internet traffic data (in bits) over time. Using RStudio I performed a Simple Trend Model, Multiplicative Classical Decomposition, Additive Classical Decomposition, and an ARIMA model.
Discretizations of Exterior Calculus for Analysis, Geometry and Topology
上海交通大学 致远数学方向 专业研讨课3 [计算神经科学专题]
Equation sheets of STEM courses at the University of Washington (UW). Topics include chemistry, physics, calculus, applied mathematics, and chemical engineering.
A review of HAVOK and Reservoir computing for chaotic dynamics forecast
[DEPRECATED] Statistics & Numerical algorithms implemented in Julia.
Gauss-Newton solver implemented from scratch.
Research in compressing convolutional layers of CNN using low-rank tensor decomposition
Code supplement for "The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models"
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