Federico Baldassarre's repositories
baldassarreFe
Personal README
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
baldassarreFe.github.io
Personal and academic website
freeipa-vbox
Virtualized FreeIPA setup with internal DNS, CA and replication.
deep-koalarization
Keras/Tensorflow implementation of our paper Grayscale Image Colorization using deep CNN and Inception-ResNet-v2 (https://arxiv.org/abs/1712.03400)
TranSalNet
TranSalNet: Towards perceptually relevant visual saliency prediction. Neurocomputing (2022)
dd2424-deep-learning
Assignments for the course DD2424 Deep Learning in Data Science at KTH 2017
deit-sparse
DeiT with sparse activation functions
web
Old website repo, now just a redirect
torchsearchsorted
Pytorch Custom CUDA kernel for searchsorted
torchgraphs
A PyTorch library for Graph Convolutional Networks.
pytorch-densenet-tiramisu
PyTorch implementation of DenseNet and FCDenseNet
vision
Datasets, Transforms and Models specific to Computer Vision
performer-gat-shapenet
Performer vs. Graph Attention Network on ShapeNet with GradCAM explanations.
yolov5
YOLOv5 in PyTorch > ONNX > CoreML > TFLite
FEP3370-advanced-ethical-hacking
DHCP exploitation with DynoRoot (CVE-2018-1111)
CVE-2018-1111
CVE-2018-1111 DynoRoot
rpl-workshop
Workshop on GPU and slurm usage at RPL (KTH)
pytorch-lightning
The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate
neurips2019
Website for the NeurIPS workshop 2019
graph-network-explainability
Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19)
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
sacred
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
graph_nets
Build Graph Nets in Tensorflow
dd2221-data-intensive-computing
Assignments for the course DD2221 Data Intensive Computing at KTH (Fall 2017)