Character-level RNN for text generation. Trained on Anna Karenina (included in /data folder)
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Updated
May 7, 2019 - Jupyter Notebook
Character-level RNN for text generation. Trained on Anna Karenina (included in /data folder)
In this project I generated my own Seinfeld TV scripts using RNNs using part of the Seinfeld dataset of scripts from 9 seasons.
Implementation of Recursive Neural Tensor Network as described in https://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf
Generate a TV script for a Simpsons episode, based on previous episodes.
The Deep Learning exercises provided in DataCamp
Sentiment Analysis using Recursive Neural Network
hippocampus volume quantification
Ideology Detection in the Indian Mass Media
Sentiment Classifier using: Softmax-Regression, Feed-Forward Neural Network, Bidirectional stacked LSTM/GRU Recursive Neural Network, fine-tuning on BERT pre-trained model. Question Answering using BERT pre-trained model and fine-tuning it on various datasets (SQuAD, TriviaQA, NewsQ, Natural Questions, QuAC)
Project of Paraphrase Identification Based on Weighted URAE, Unit Similarity and Context Correlation Feature
Exploiting Multi-Layer Features Using a CNN-RNN Approach for RGB-D Object Recognition (ECCV 2018 workshops)
When CNNs Meet Random RNNs: Towards Multi-Level Analysis for RGB-D Object and Scene Recognition (CVIU 2022)
A Tree-LSTM-based dependency tree sentiment labeler
Tree Stack Memory Units
[CVPR'19] Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction
Recursive Neural Networks for PyTorch
Tensorflow based solution for Assignment-3 (Recursive Neural Nets) from CS224d: Deep learning for Natural Language Processing.
Combining Symbolic and Function Evaluation Expressions In Neural Programs
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