Closed-form Continuous-time Neural Networks
-
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
AWS Last Mile Route Sequence Optimization
STCN: Stochastic Temporal Convolutional Networks
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
Controllable Sequence Editing for Counterfactual Generation
USE: Dynamic User Modeling with Stateful Sequence Models
Repository for the Paper: „On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series“
A dataset utils repository based on tf.data API.
French English Machine Translation. Natural language processing (NLP) transformer model from "Attention Is All You Need"
An out-of-the-box long-text NLP framework.
Code for the ExpectoSC model
Add a description, image, and links to the sequence-models topic page so that developers can more easily learn about it.
To associate your repository with the sequence-models topic, visit your repo's landing page and select "manage topics."