Topic: "deep-learning-architectures"
mead-ml/mead-baseline
Deep-Learning Model Exploration and Development for NLP
Language: Python - Size: 11.2 MB - Last synced at: 9 days ago - Pushed at: over 1 year ago - Stars: 243 - Forks: 73
gmh14/RobNets
[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks
Language: Python - Size: 324 KB - Last synced at: 5 months ago - Pushed at: over 4 years ago - Stars: 123 - Forks: 15
Totoketchup/Adaptive-MultiSpeaker-Separation
Adaptive and Focusing Neural Layers for Multi-Speaker Separation Problem
Language: Jupyter Notebook - Size: 18 MB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 45 - Forks: 18
ashishsalunkhe/DeepSpamReview-Detection-of-Fake-Reviews-on-Online-Review-Platforms-using-DeepLearning-Architectures
DeepSpamReview: Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures. Summer Internship project at CoreView Systems.
Language: Jupyter Notebook - Size: 1020 KB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 40 - Forks: 12
mike-gimelfarb/cascade-correlation-neural-networks
A general framework for cascade correlation architectures in Python with wrappers to keras, tensorflow and sklearn
Language: Python - Size: 833 KB - Last synced at: 17 days ago - Pushed at: 4 months ago - Stars: 12 - Forks: 4
basiralab/GSR-Net
Graph SuperResolution Network using geometric deep learning.
Language: Python - Size: 16.3 MB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 11 - Forks: 0
nutellamok/advrush
Official Code for AdvRush: Searching for Adversarially Robust Neural Architectures (ICCV '21)
Language: Python - Size: 45.9 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 10 - Forks: 3
SaashaJoshi/deep-learning-architectures
Deep Learning architectures in Tensorflow Keras, and PyTorch.
Language: Jupyter Notebook - Size: 194 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0
yskim0/pytorch-cifar10
Implementing and training/testing popular model architectures on the CIFAR10 dataset.
Language: Python - Size: 15.6 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 2
vishal-keshav/xcelerator
Exploring RL ideas for deep neural network hyper-parameter search
Language: Python - Size: 205 KB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 2 - Forks: 1
jmaczan/deep-learning-pytorch
Deep Learning architectures implemented in PyTorch Lightning
Language: Python - Size: 110 KB - Last synced at: 2 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0
HasibAlMuzdadid/Deep-Learning-Papers-Reading-Roadmap Fork of floodsung/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who is eager to learn this amazing tech!
Language: Python - Size: 3.48 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0
MLD3/MLHC2018_SequenceTransformerNetworks
Code release for "Learning to Exploit Invariances in Clinical Time-Series Data Using Sequence Transformer Networks" (Oh, Wang, Wiens), MLHC 2018. https://arxiv.org/abs/1808.06725
Language: Python - Size: 3.91 KB - Last synced at: almost 2 years ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 1
MLD3/MLHC2019_Relaxed_Parameter_Sharing
Code release for "Relaxed Weight Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series" (Oh, Wang, Tang, Sjoding, Wiens), MLHC 2019. https://arxiv.org/abs/1906.02898
Language: Python - Size: 61.5 KB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0
Morin3/storybook Fork of storybookjs/storybook
Storybook is the industry standard workshop for building, documenting, and testing UI components in isolation
Size: 738 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0
Morin3/hash-toolbox Fork of hashim21223445/hash-toolbox
# Andoka-2 H.5 Andoka now TV
Language: JavaScript - Size: 501 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
Ishan-Kotian/Tokenizer_NLP
Tokenization is a way of separating a piece of text into smaller units called tokens. Here, tokens can be either words, characters, or subwords. Hence, tokenization can be broadly classified into 3 types – word, character, and subword (n-gram characters) tokenization.
Language: Jupyter Notebook - Size: 60.5 KB - Last synced at: about 2 months ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0
AkhithaBabu/Notes
Notes on ML and DL with jupyter notebooks (python)
Language: Jupyter Notebook - Size: 6.27 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0
Dheeraj2444/keras-examples
My experimentations with Keras
Language: Jupyter Notebook - Size: 467 KB - Last synced at: over 1 year ago - Pushed at: about 7 years ago - Stars: 0 - Forks: 1
Aayush-Ankit/ece595z-design-automation
Language: Python - Size: 59.4 MB - Last synced at: about 2 years ago - Pushed at: almost 8 years ago - Stars: 0 - Forks: 0
