Name: Jirayu Petchhan
Type: User
Company: National Taiwan University of Science and Technology
Bio: Jonathan, Postdoc research associate, Intelligent Systems and Control lab, EE dept., Taiwan Tech
Interests: transfer learning, AIoT, & industry application.
Twitter: 0xJoe_atqr
Location: Taipei City
Blog: https://www.linkedin.com/in/jirayu-petchhan-3b4544195/
Jirayu Petchhan's Projects
Code and hyperparameters for the paper "Generative Adversarial Networks"
A collection of AWESOME things about domian adaptation
Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2020)。
This repo is the part of course documents and project assigned in Blockchain course (109.2【工管系】IM6313701 區塊鏈理論與實務 Theory and Practice of Blockchain), Taiwan Tech.
implement for paper Rethinking Domain Adaptation Blending target Domain Adaptation by Adversarial Meta Adaptation Network
Classifying Facial Attributes and Accessories with LeNet base on TensorFlow 2.0 framework (NOOB project)
This repo is the part of exercise in 109.2 ME5617702 Computer Vision for Home Security and Application, Taiwan Tech.
Data Efficient Model Compression
Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.
This repo is the part of exercise in 109.1【機械系】ME5617701 數位監控系統與應用 Digital Surveillance Systems and Application, Taiwan Tech.
A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.
An implementation of the paper "Learning to Reweight Examples for Robust Deep Learning" from ICML 2018 with PyTorch and Higher.
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
Pytorch implementation of MirrorGAN
Official implementation of PCS in essay "Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation"
Config files for my GitHub profile.
IIoT class : hands-om #1 (WeMos with Blynk platform)
A collection of implementations of adversarial domain adaptation algorithms
PyTorch implementations of Generative Adversarial Networks.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
An implementation of Deep Adaptation Network with pytorch
PyTorch Implementation for ResNet, Pre-Activation ResNet, ResNeXt and DenseNet
Library package for installing first time.
Transformers for Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
PyTorch Implementation for SoftTriple Loss
Official implementation of STOS in an original article "High-intensified resemblance & Statistic-Restructured Alignment in Few-Shot DA for Industrial-Specialized Employment"
Knowledge Distillation: CVPR2020 Oral, Revisiting Knowledge Distillation via Label Smoothing Regularization
Everything about Transfer Learning and Domain Adaptation--迁移学习
PyTorch tutorials.