AI in-depth material

Interpretability for sequence generation models 🐛 🔍

An AI assistant for a Learning Management System (LMS)

This Project is based on multilingual Translation by using the Transformer with an encoder-decoder architecture along with the multi-head self-attention layers with the positional encoding and embedding for better result and accuracy. Overall, this model converts the English to French language using various Techniques of NLP and DL.

A library for open domain query facet extraction and generation

Solution to im2latex request for research of openai

The First version of the first AI First Aid application release 1.0

DELTA is a deep learning based natural language and speech processing platform.

Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported, cross-platforms (Windows, Linux, x86, x64, ARM), multimodal model for text and images and so on.

a dna sequence generation/classification using transformers

A T5-based Seq2Seq Model that Generates Titles for Machine Learning Papers using the Abstract

Continuous learning applied to the development of a Chatbot based on Sequence-To-Sequence architecture

A game of strategy and observation, can you find all the matching numbers and become the ultimate number checker champion?

Sequence-to-sequence framework with a focus on Neural Machine Translation based on PyTorch

A few approaches using sequence to sequence (seq2seq) architecture to solve semantice parsing problem

A sequence-to-sequence voice conversion toolkit.

[ICLR'23] DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models

The implementation of the paper "Augmenting Neural Response Generation with Context-Aware Topical Attention"

YAI 11 x @POZAlabs : Music generation & modification from Unclear midi SEquence with Diffusion model

Apply deep learning model to generate text summaries in the form of short news articles using sequence to sequence (LSTM) model.