deep-learning

DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.

Phoneme Recognition using pre-trained models Wav2vec2, HuBERT and WavLM. Throughout this project, we compared specifically three different self-supervised models, Wav2vec (2019, 2020), HuBERT (2021) and WavLM (2022) pretrained on a corpus of English speech that we will use in various ways to perform phoneme recognition for different languages with a network trained with Connectionist Temporal Classification (CTC) algorithm.

PyTorch implementation of Transformer model used in "Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case"

From scratch implementation of a vision language model in pure PyTorch

PyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

AI assistant that can query visual datasets, search the FiftyOne docs, and answer general computer vision questions

PyTorch template for Deep Learning projects with support for scalable multi-GPU and multi-node training.

Code for the paper 'Learning TSP Requires Rethinking Generalization' (CP 2021)

Deep-Learning Model Exploration and Development for NLP

A Continuously Updated Library for Advanced Models for Multimodal Recommendation

A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.

Graphsignal Profiler

A Keras CTC implementation of Baidu's DeepSpeech for model experimentation

Custom APRL machine-learning algorithm + a curated ML knowledge base of 923 papers, lectures, and explainers. NumPy classifier/regressor, tests, benchmarks, provenance, Obsidian, and agent-ready Markdown.

HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!😊 HugNLP will released to @HugAILab

[CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"

[ICLR 2026] Uni-CoT: Towards Unified Chain-of-Thought Reasoning Across Text and Vision

Annotated Flow Matching paper

Deep-Learning framework for Engineering AI. Built on transformer building blocks, it delivers the full engineering stack, allowing teams to build, train, and operate industrial simulation models across engineering verticals.

【2023年版】BERTによるテキスト分類