Jude TCHAYE's repositories
Awesome-Federated-Learning
Federated Learning Library: https://fedml.ai
BIT-Report-LaTeX
English and Chinese LaTex template for reports/projects/proposal at Beijing Institute of Technology
EfficientNet-PyTorch
A PyTorch implementation of EfficientNet
federated-learning
A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561
flower
Flower - A Friendly Federated Learning Framework
GraphEmbedding
Implementation and experiments of graph embedding algorithms.
Halite
Kaggle Halite RL challenge - Provisional first place solution
Image-Rotation-and-Cropping-tensorflow
Image rotation and cropping out the black borders in TensorFlow
keras-arcface
Keras implementation of ArcFace, CosFace, and SphereFace
keras-rl
Deep Reinforcement Learning for Keras.
keras-YOLOv3-model-set
end-to-end YOLOv4/v3/v2 object detection pipeline, implemented on tf.keras with different technologies
kerasutils
My Keras models utils
longformer
Longformer: The Long-Document Transformer
orcidlink-LaTeX-command
LaTeX style file to add a macro for inserting a linked ORCiD logo
pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Periodic-Table-JSON
A json of the entire periodic table.
pFedMe
Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)
pointer-networks
Pointer Networks Implementation in Keras
PyTorch-Raspberry-Pi-Files
PyTorch Raspberry Pi .whl files
RandomizedResponse
Applies a randomized response to the input. The RandomizedResponse layer randomly sets input units to random values with a frequency of rate at each step during training time, which helps prevent overfitting.
resize_network_cv
PyTorch implementation of the paper "Learning to Resize Images for Computer Vision Tasks" on Imagenette and Imagewoof datasets
rl-bot-football
An RL agent for the Google Football environment
seed_rl
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
torchutils
My torch models training utilities
UNet-Segmentation-AutoEncoder-1D-2D-Tensorflow-Keras
Models Supported: UNet, UNet-Ensembled, UNet+, UNet++, MultiResUNet (with Deep Supervision, Guided Attention, and Autoencoder modes for 1D or 2D).