Python package for AdaS: Adaptive Scheduling of Stochastic Gradients
Gradient boosted decision tree palindrome predictor, used to locate regions for further investigation thru http://palindromes.ibp.cz/
Method PROTES (PRobabilistic Optimizer with TEnsor Sampling) for derivative-free optimization of the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format
GrafoRVFL: A Gradient-Free Optimization Framework for Boosting Random Vector Functional Link Network
A python package containing implementations of two widely used algorithms to minimise any function - Gradient Descent algorithm and the Normal Equation method.
Leap Frog Optimizer
StructureBoost is a Python package for gradient boosting using categorical structure. See documentation at: https://structureboost.readthedocs.io/
Medical Deep Learning Framework.
Medical Deep Learning Framework
Medical Deep Learning Framework
RNN and general weights, gradients, & activations visualization in Keras & TensorFlow
Python Sensitivity Analysis - Gradient DataFrames and Hex-Bin Plots
Magnetic Field Coil Generator for Python.
Stochastic optimization routines for Theano
PyTorch optimizer based on nonlinear conjugate gradient method
Stochastic Gradient Monte Carlo in Jax
A wrapper of scipy minimize with automatic gradient and hessian computation.
A module for Data Assimilation and Optimization
RotoGrad: Gradient Homogenization in Multitask Learning in Pytorch
Field and gradient calculations for magnetic coils
Deep Neural Network inspection: view weights, gradients and activations
Fast (and cheeky) differentially private gradient-based optimisation in PyTorch
Artificial Neural Network
Functions and classes for gradient-based robot motion planning, written in Ivy.
Multiobjective black-box optimization using gradient-boosted trees
A python package for the Cyclic Gradient Boosting Machine algorithm
Automatic-Class-Balanced MSE Loss for PyTorch (ACB-MSE) to combat class imbalanced datasets and stabilise fluctuating loss gradients.
growingnn is a cutting-edge Python package that introduces a dynamic neural network architecture learning algorithm. This innovative approach allows the neural network to adapt its structure during training, optimizing both weights and architecture. Leveraging a Stochastic Gradient Descent-based optimizer and guided Monte Carlo tree search, the package provides a powerful tool for enhancing model performance.
Hyperparameter optimization via gradient boosting regression
Compute Friedman and Popescu's H statistics, in order to look for interactions among variables in scikit-learn gradient-boosting models.
A pytorch library that implements differentiable and learnable robot models, which allows users to learn parameters of analytical robot models, and/or propagate gradients through analytical robot computations such as forward kinematics.
Conjugate Gradient SENSE (CG-SENSE) MRI Reconstruction
Directed evolution of proteins with fast gradient-based discrete MCMC.
Implementation of Cumulative Spectral Gradient (CSG), a measure to estimate the complexity of datasets. This works has been presented at CVPR 2019.
Gradient Index (GRIN) Lens Calculations
Enhanced Integrated Gradients - a method of attributing the prediction of a deep network to its input features
Nano size theano lstm module
Train a gradient boosted tree to predict the salary of US residents from a salary-related survey dataset
A module to genereate gradient text and rich panels.
A package for automating machine learning tasks
Light Propagation in Optical Fibers
fast calculation of sparse gradients and Jacobian matrices in Python
Gradient-based boundary (GBB) surface refinement
Leap Frog Optimizer - Lite Edition
A Library of Linear and Logistic Regression with Genetic algorithm instead of Gradient Descent
The Simple Pytorch-Like Auto Differentiation Toolkit is an automatic differentiation package for calculating gradients of a function in forward and reverse mode.
Smart gradient clippers
A model agnostic and gradient-free optimization method for generating counterfactuals