Meta-meta-learning with evolution and plasticity

Overview

Meta-meta-learning with evolution and plasticity

This is the code for the arxiv preprint Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning.

We evolve plastic networks to be able to automatically acquire novel cognitive (meta-learning) tasks, that were not seen during training.

The code is in the form of Jupyter notebooks that can be run on Google Colab. It is strongly recommended to consult the Simple notebook, which contains a simplified version of the code that should be easier to read through, while still producing the same results. The other notebook contains the full code that was actually used to run the experiments.

This is the paddle code for SeBoW(Self-Born wiring for neural trees), a kind of neural tree born form a large search space

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Demonstration of the Model Training as a CI/CD System in Vertex AI

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Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks

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Trax — Deep Learning with Clear Code and Speed

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Unsupervised clustering of high content screen samples

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git《Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction》(ECCV 2020) GitHub:

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Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder

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Example repository for custom C++/CUDA operators for TorchScript

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Offical implementation for "Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection Separation".

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Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano

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GB-CosFace: Rethinking Softmax-based Face Recognition from the Perspective of Open Set Classification

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This repository focus on Image Captioning & Video Captioning & Seq-to-Seq Learning & NLP

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Machine Learning Models were applied to predict the mass of the brain based on gender, age ranges, and head size.

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Complete system for facial identity system

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Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"

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NIMA: Neural IMage Assessment

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