Awesome list for Neural Network Optimization methods.
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Updated
Mar 10, 2024
Awesome list for Neural Network Optimization methods.
Stochastic gradient descent with model building
[Neurips 2022] "Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis" by Wuyang Chen*, Wei Huang*, Xinyu Gong, Boris Hanin, Zhangyang Wang
Worth-reading papers and related awesome resources on deep learning optimization algorithms. 值得一读的深度学习优化器论文与相关资源。
Implementation and comparison of zero order vs first order method on the AdaMM (aka AMSGrad) optimizer: analysis of convergence rates and minima shape
A Python math package for numerical analysis: root finding, iterative solvers & other algorithms. Bisection, Newton, Euler, RK2, RK4, Adams-Bashforth-Moulton, etc. Uses Python, NumPy, SymPy, pytest.
Collection of methods for numerical analysis and scientific computing, including numerical root-finders, numerical integration, linear algebra, and data visualization. Created for APPM4600 at CU Boulder.
Some VASP processing and convergence-testing shell scripts.
[EE580: Network System - Modelling & Analysis] This repo contains all the assignment of EE580 offered at IIT Mandi by Dr.Sreelakshmi Manjunath during Fall Session 2023.
Toy models for Cauchy-Characteristic Extraction (CCE) and Matching (CCM)
Implementation and evaluation of the Ant Colony Optimization algorithm on the bin-packing problem
Alpha Belief Propagation
Special Project - CA classification (2019 Fall)
Record of Gachon Convergence Research Assistant
Official code repository for "Penalized MLE of multi-layer Gaussian Graphical Models"
Analysis of simulation data obtained with the ParMooN finite element package.
Bayesian inference tools, allowing to execute Gibbs sampling and run some diagnostics on results.
Differential Evolution Algorithm to minimize a function
StoMADS algorithm for stochastic blackbox optimization
[Optimization algorithms] Study of the Proximal Gradient Method, Stochastic Gradient Descent method and Adam optimizer
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