xwasco
Assistant Professor at Ca' Foscari University of Venice working in the fields of machine learning, computer vision and deep learning.
Ca' Foscari University of VeniceVenice, Italy
Pinned Repositories
Afternotes
Afternotes for the attended courses at Ca' Foscari University, master in Data Management and Analytics.
ams-2020-ml-python-course
Materials for the Machine Learning in Python for Environmental Science Problems AMS 2020 Short Course
cs231n.github.io
Public facing notes page
DAISGram_20_21
Repository per il progetto di Laboratorio di Programmazione A.A. 2020-2021
deep-active-learning
Deep Active Learning
deep-person-reid
Pytorch implementation of deep Person Re-Identification models.
deepALplus
This is a toolbox for Deep Active Learning, an extension from previous work https://github.com/ej0cl6/deep-active-learning (DeepAL toolbox).
DominantSetLibrary
A Matlab library for the Dominant Set clustering
GTCG
Game-Theoretic Conversational Groups Detector - CVIU2015/ACCV2014
GTNMF
Context-aware non negative matrix factorization clustering. ICPR2016
xwasco's Repositories
xwasco/DominantSetLibrary
A Matlab library for the Dominant Set clustering
xwasco/DAISGram_20_21
Repository per il progetto di Laboratorio di Programmazione A.A. 2020-2021
xwasco/GTCG
Game-Theoretic Conversational Groups Detector - CVIU2015/ACCV2014
xwasco/pyDominantSets
Pytorch Implementation of Dominant Sets
xwasco/Afternotes
Afternotes for the attended courses at Ca' Foscari University, master in Data Management and Analytics.
xwasco/cs231n.github.io
Public facing notes page
xwasco/deepALplus
This is a toolbox for Deep Active Learning, an extension from previous work https://github.com/ej0cl6/deep-active-learning (DeepAL toolbox).
xwasco/DeepLabv3FineTuning
Tutorial on fine tuning DeepLabv3 segmentation network for your own segmentation task in PyTorch.
xwasco/DeepLearningExamples
Deep Learning Examples
xwasco/dgl-ke
High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.
xwasco/GNNPapers
Must-read papers on graph neural networks (GNN)
xwasco/introduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"
xwasco/latent-diffusion
High-Resolution Image Synthesis with Latent Diffusion Models
xwasco/Machine-Learning-Book-Collections
xwasco/MEMEX-KG
Connecting targeted communities to experiences and memories with a new Knowledge Graph (KG) for Cultural Heritage.
xwasco/MVA_2023_SL
Course materials for the MVA course "algorithms for speech and language processing"
xwasco/NeMo
NeMo: a toolkit for conversational AI
xwasco/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
xwasco/pytorch-Deep-Learning
Deep Learning (with PyTorch)
xwasco/pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
xwasco/PyTorch_CIFAR10
Pretrained TorchVision models on CIFAR10 dataset (with weights)
xwasco/Semi-supervised-learning
A Unified Semi-Supervised Learning Codebase (NeurIPS'22)
xwasco/slurm_gpu_ubuntu
Instructions for setting up a SLURM cluster using Ubuntu 18.04.3 with GPUs.
xwasco/ssn-pytorch
PyTorch implementation of Superpixel Sampling Networks
xwasco/stable-diffusion
A latent text-to-image diffusion model
xwasco/starter-hugo-academic
xwasco/Trajectron-plus-plus
Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).
xwasco/VT-ADL
A Vision Transformer Network for Image Anomaly Detection and Localization
xwasco/website
xwasco/xwasco.github.io
Personal Website