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
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.
Implementation and comparison of zero order vs first order method on the AdaMM (aka AMSGrad) optimizer: analysis of convergence rates and minima shape
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。
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.
Official implementation of "Unraveling the Hessian: A Key to Smooth Convergence in Loss Function Landscapes"
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.
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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