Stars
NYU's Introduction to Deep Learning Research
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
Help augment diagnostic workflows with this Databricks Solution Accelerator for pathology image analysis. Now you can rapidly process thousands of whole slide images in minutes and use machine lear…
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
Implementation of Attention-based Deep Multiple Instance Learning in PyTorch
Prediction of B-cell epitopes from amino acid sequences using deep neural networks.
Repository containing all the custom codes from the study: "NF1 modulates microtubular repair and dictates sensitivity to maytansinoid antibody-drug conjugates in HER2-positive breast cancer".
Companion project to the publication A FZD7-specific antibody-drug conjugate induces solid tumor regression in preclinical models by Myan Do et al.
Deep learning models and structure realization scripts for the DeepAb antibody structure prediction method.
Protein design and variant prediction using autoregressive generative models
Learn how to develop, deploy and iterate on production-grade ML applications.
A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputatio…
Repository for the paper: 'Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models'
Impute missing flux data using ML/DL
Performance of the EM algorithm and imputation methods with different missing data mechanisms (EPFL - Statistical Computation and Visualization)
Tutorials and example projects for building applications using generative AI.
Awesome Deep Learning for Time-Series Imputation, including an unmissable paper and tool list about applying neural networks to impute incomplete time series containing NaN missing values/data
An up-to-date list of time-series related papers in AI venues.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
a Python toolbox loads 172 public time series datasets for machine/deep learning with a single line of code. Datasets from multiple domains including healthcare, financial, power, traffic, weather,…
A library for Multilingual Unsupervised or Supervised word Embeddings
TensorFlow code and pre-trained models for BERT