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jin's Projects

adamp icon adamp

Slowing Down the Weight Norm Increase in Momentum-based Optimizers

ai-edu icon ai-edu

AI education materials for Chinese students, teachers and IT professionals.

artificial-bee-colony icon artificial-bee-colony

A python implementation of clustering optimization using the Artificial Bee Colony algorithm

auto-gpt icon auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

autodl-projects icon autodl-projects

Automated deep learning algorithms implemented in PyTorch or Tensorflow.

awesome-automl-and-lightweight-models icon awesome-automl-and-lightweight-models

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

awesome-deep-neuroevolution icon awesome-deep-neuroevolution

A collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)

awesome-nas icon awesome-nas

A curated list of neural architecture search (NAS) resources.

bayesian-automl icon bayesian-automl

Este es un experimento de un par de horas, probablemente de a poco le empiece a dar forma

bayesian-neural-networks icon bayesian-neural-networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

benchmarkfcns icon benchmarkfcns

A collection of mathematical test functions for benchmarking optimization algorithms.

celluloid icon celluloid

Celluloid: clustering single cell sequencing data around centroids

continuousparetomtl icon continuousparetomtl

[ICML 2020] PyTorch Code for "Efficient Continuous Pareto Exploration in Multi-Task Learning"

d3-force-3d icon d3-force-3d

Force-directed graph layout in 1D, 2D or 3D using velocity Verlet integration.

data-science-from-scratch icon data-science-from-scratch

Experimenting with the code examples from the book "Data Science from Scratch: First Principles with Python"

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