MaskPlanner is a deep learning model for the quick generation of multiple, long-horizon paths from free-form 3D objects represented as point clouds.

PaintNet: Unstructured Multi-Path Learning from 3D Point Clouds for Robotic Spray Painting

Collection of gym environments with support for domain randomization

Starting code for course project of MLDL 2024 - 01TXFSM, Polytechnic of Turin.

Reset-Free DROPO

Domain Randomization via Entropy Maximization

Slurm experiments launcher for python scripts

DROPO: Sim-to-Real Transfer with Offline Domain Randomization

Interface to stable-baselines3 APIs for training RL policies on gym-registered environments

Online vs. Offline Adaptive Domain Randomization Benchmark

Starting code for the course project of Advanced Machine Learning in Reinforcement Learning

Starting code for exam project of Data Analysis and Artificial Intelligence 2022 course @ Politecnico di Torino

Starting code template for the course project in sim-to-real for reinforcement learning in robotics (machine learning and deep learning 2022 course).

Open online Full Stack Web Developer course at Aalto University

Part 3 exercises of Full Stack Web Developer open online course

Reproduction of popular methods for class-incremental learning in image recognition and proposal of a new variant.

Implementation of popular reinforcement learning control algorithms to build an intelligent pong player.

Comparison of traditional shallow machine learning techniques for a classification task on the UCI Wine dataset.

Shallow machine learning techniques have been analysized and applied for a data-driven diagnosis of Parkinson's desease from patient voice measurements.

Training of a Convolutional Neural Network for image classification on dataset Caltech-101 by using AlexNet structure with both transfer learning and not.

Implementation of DANN, a Domain Adaptation algorithm, on the PACS dataset using AlexNet.

Binary classification of textual data with traditional ML techniques to predict the mood of a real-world review (positive or negative).