Deep-Learning Model Exploration and Development for NLP
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Updated
Oct 13, 2023 - Python
Deep-Learning Model Exploration and Development for NLP
Adaptive and Focusing Neural Layers for Multi-Speaker Separation Problem
[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks
DeepSpamReview: Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures. Summer Internship project at CoreView Systems.
Deep learning architectures for in-air hand gesture recognition
Official Code for AdvRush: Searching for Adversarially Robust Neural Architectures (ICCV '21)
Implementing and training/testing popular model architectures on the CIFAR10 dataset.
My experimentations with Keras
Exploring RL ideas for deep neural network hyper-parameter search
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
🌻 Deep Learning models implemented in PyTorch Lightning
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.
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
# Andoka-2 H.5 Andoka now TV
Graph SuperResolution Network using geometric deep learning.
Notes on ML and DL with jupyter notebooks (python)
Deep Learning papers reading roadmap for anyone who is eager to learn this amazing tech!
Deep Learning architectures in Tensorflow Keras, and PyTorch.
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