Closed-form Continuous-time Neural Networks
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Updated
Jul 5, 2024 - Python
Closed-form Continuous-time Neural Networks
Full named-entity (i.e., not tag/token) evaluation metrics based on SemEval’13
A Tensorflow based implicit recommender system
STCN: Stochastic Temporal Convolutional Networks
AWS Last Mile Route Sequence Optimization
Code and pretrained models for the paper: "MatMamba: A Matryoshka State Space Model"
Structured Prediction Helps 3D Human Motion Modelling - ICCV '19
CREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.
Abstractive text summarization by fine-tuning seq2seq models.
Official implementation of DenoMamba: A fused state-space model for low-dose CT denoising
Deep Recurrent Model for Individualized Prediction of Alzheimer’s Disease Progression - PyTorch Implementation (NeuroImage 2021)
Official implementation of MambaRoll: A Physics-Driven Autoregressive State Space Model for Medical Image Reconstruction (https://arxiv.org/abs/2412.09331)
Lyrics crawling, pre-processing, embedding generation, model training, and lyrics generation - all in one tool
Repository for the Paper: „On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series“
Controllable Sequence Editing for Counterfactual Generation
USE: Dynamic User Modeling with Stateful Sequence Models
A dataset utils repository based on tf.data API.
Play The Piano With Deep Learning 用深度学习弹钢琴 2019-5-22
Sentiment analysis for amazon product reviews using NLTK, Scikit-Learn, and Keras. Using hyperparameter search and LSTM, our best model achieves ~96% accuracy.
French English Machine Translation. Natural language processing (NLP) transformer model from "Attention Is All You Need"
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