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Top Repositories
Data-free knowledge distillation using Gaussian noise (NeurIPS paper)
PyTorch implementation of Variational Continual Learning
OpenAI_gym-CarRacing-v0 Supervised Learning
Foundational models for fast simulation
Relevant papers in Continual Learning
Repositories
41Official DeiT repository
Foundational models for fast simulation
Weak Lensing Cosmology Challenge Repository
particle-flow with ml
PyTorch implementation of Variational Continual Learning
HEP Software Foundation github site
No description provided.
Foundation Model for Fast Shower Simulation
Data-free knowledge distillation using Gaussian noise (NeurIPS paper)
No description provided.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
No description provided.
A pytorch implementation of MINE(Mutual Information Neural Estimation)
No description provided.
PyTorch Implementation of Weights Pruning
Examples and use cases using the deepbots framework (https://github.com/aidudezzz/deepbots) with the Webots robot simulator.
Tutorials for the deepbots framework https://github.com/aidudezzz/deepbots
A wrapper framework for Reinforcement Learning in Webots simulator using Python 3.
No description provided.
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Machine Learning meets ketosis: how to effectively lose weight
Experiments with the ideas presented in https://arxiv.org/abs/2003.00152 by Frankle et al.
This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.
No description provided.
Implementation of the variational continual learning method
Relevant papers in Continual Learning
OpenAI_gym-CarRacing-v0 Supervised Learning
NumPy-like API accelerated with CUDA
No description provided.
No description provided.