Sequence modelling applied to event collisions
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Updated
Jun 12, 2019 - Python
Sequence modelling applied to event collisions
Differentiable Sequence Models
Code for my solution to the Google Quickdraw Doodle Recognition Challenge
Code for the ExpectoSC model
Generate music with LSTM model
The repo contains the implementation of my publication GAN-Poser:
A dataset utils repository based on tf.data API.
Implementation of Transformer Network
Jax/Flax/Linen implementation of "Simple Hardware-Efficient Long Convolutions for Sequence Modeling"
Prototypes for EHR-sequencing and temporal phenotyping. Key methods: sequence models, LSTM, attention mechanism, cluster analysis, word & document embeddings, and other NLP methods.
Final project of Natural Language Understanding course at University of Trento, in which I tackle sentiment analysis with various deep sequence models and transformers.
Various RNN/Sequence model projects I work(ed) on
Simple implementations of long-range sequence models (LRU, S5, S4, and more).
Quinn: Complex Word Identification using Neural Networks (CWI-NN)
Repository for the Paper: „On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series“
This is a sentiment classifier using LSTM with attention custom estimator in Tensoflow
Models for frame-wise video regression
Play The Piano With Deep Learning 用深度学习弹钢琴 2019-5-22
Using Recurrent Neural Networks for the handwritten digit classification on MNIST dataset.
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